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{{#Wiki_filter:SUSQUEHANNA SES-ER-OL SECTIONTITLEVOLUMEAPPENDX'XZS....~.............
{{#Wiki_filter:SUSQUEHANNA SES-ER-OL SECTION TITLE VOLUME APP EN DX'XZS....~.............
~XIIB1ANEVALUAONOFTHECOSTOFSF.VICEIMPACTOFADELAYNTHEIN-SERVICE DTESOFSUSQUEHANNA ES(JANUARY1978............IXI CURRENTLONG-RAGEFORECASENERGYSALES6PEAKLOAD1976-10....................
~XII B1 AN EVALUA ON OF THE COST OF SF.VICE IMPACT OF A DELAY N THE IN-SERVICE D TES OF SUSQUEHANNA ES (JANUARY 1978............IXI CURRENT LONG-RA GE FORECAS ENERGY SALES 6 PEAK LOAD 1976-1 0....................
~~IXIAPPLICANT'S FORECASNGMETHODOLOGY KMHSALESANDPEAKLOADSCE!1BER,1976.........IXI NATXONMIDE FUELEilZGENCYZSPONSZTOFPCORDERNO496..............
~~IXI APPLICANT'S FORECAS NG METHODOLOGY KMH SALES AND PEAK LOADS CE!1BER, 1976.........IXI NATXONMIDE FUEL EilZ GENCY ZSPONSZ TO FPC ORDER NO 496..............
~XIISUSQUEHANNA RIVEMATERANALYSZSUMMARY..IIIEQUATIONS ANDSSUMPTIONS UTILIZEDNTHECALCULATION 0INDIVIDUAL ANDPOPULAONDOSESTOMAN.'IXENVIRON%EN ALTECHNXCALSPECIFXCATIONS..XII SUSQUEHANNA SES-ER-OL TABLE1.1-31977PROJECTION OFAPPLICAN'A LOADS-CAPACITY-RESERVES (HIGHLOADPROJECTION YearWinterPeakMWe1978496019795320198056701981610019826480198368401984720019857570CapacityChangesFossil(Oil)NuclearHydroReratings 945(')945(l)63(2)TotalCapacities Fossil(Coal)Fossil(Oil)CT6(j~selHydroNuclearFirmPurchaseCapacityTransactions 4145164053914676(41)4145164053914676(50)4145164053914676414516405391461890764145414541454145164016401640164053953953953914614614620994518901890189076767676TotalMWe65056496643674268405837483438374Reserveoverwinterpeak:WithSusquehanna MWeCapacityXofLoad132622192530153411432216804llWithoutSusquehanna MWeCapacity%ofLoad154531117622766143265(65)(436)(807)(1126)(1)(6)(ll)(15)WithSusquehanna ButWithoutOilSHydroGeneration WithoutSusquehanna~
~XII SUSQUEHANNA RIVE MATER ANALYSZ
Oil8HydroGeneration HweCapacity(856)(1225)(17)(23)(1075)(476)(867)(1258)(1660)(18)(7)(13)(17)(22)(1635)(2075)(2466)(2837)(3208)(3590)(29)(34)(38)(41)(45)(47)Note:SeeFootnotes Following Table1.1-6.
SUSQUEHANNA SES"ER-OL TABLE1.1-41977PROJECTION OFAPPLICAFA LOADS-CAPACITY-RESERVES MID-RANGE LOADPROJECTION)
YearWinterPeakMWeCapacityChangesFossil(Oil)NuclearHydroReratings 19784820197950501980531019815690945(l)19825990945"'9836280198465601985685063(2)TotalCapacities Fossil(Coal)Fossil(Oil)CT6(j~selHydroNuclearFirmPurchaseCapacityTransactions TotalMWe4145164053914676(41)65054145164053914676(50)64964145164053914676~(11064364145164053914694576(65)742641451640539146189076(31)840541451640539146189076(62)83744145164053914618907641451640539209189076~(93(125)83438374Reserveoverwinterpeak:WithSusquehanna MWeCapacitygofLoad17362415314020943317831524'2722WithoutSusquehanna MWeCapacity$ofLoad1685144635291126217361342571242(167)(406)(3)(6)WithSusquehanna ButWithoutOil6HydroGeneration (665)(12)14(307)(618)(940)1(5)(9)(14)WithoutSusquehanna~
Oil6HydroGeneration (716)(955)(1275)(1665)(1976)MweCapacity(15)(19)(24)(29)(33)NOTE:SeeFootnotes Following Table1.1-6(2277)(2568)(2870)(36),(39)(42)


SUS(UEHANNA SES-ER-OL TABLE1.1-51977PROJECTION OFAPPLICANT LOADS-CAPACITY"RESERVES (IOWIOADPROJECTION YearWinterPeakMWeCapacityChangesFossil(Oil)NuclearHydroReratings 19784650197947201980491019815170945"'9825390945("19835650198459201985605063(2)TotalCapacities Fossil(Coal)Fossil(Oil)CT8(j~selHydroNuclearFirmPurchaseCapacityTransactions TotalMwe4145164053914676414516405391467641451640539146764145164053914694576414541454145164016401640539539539146146146189018901890767676650564966436742684058374834341451640539146189076(125)8374Reserveoverwinterpeak:WithSusquehanna MWeCapacity~ofLoad225630154456272448242323244138WithoutSusquehanna MWeCapacity4ofLoadWithSusquehanna ButWithoutOil6HydroGeneration MWeCapacitygofLoad185517761526403831(145)(3)6141112561025241975413323647382213947(140)(2)WithoutSusquehanna>
==SUMMARY==
Oil8HydroGeneration (546)(625)MWeCapacity(12)(13)gofLoadNOTE:SeeFootnotes Following Table1.1-6.(875)(1145)(1376)(1647)(18)(22)(26)(29)(1928)(2070)(33)i(34)
..III EQUATIONS AND SSUMPTIONS UTILIZED N THE CALCULATION 0 INDIVIDUAL AND POPULA ON DOSES TO MAN.'IX ENVIRON%EN AL TECHNXCA L S PECIFXC ATION S..XII SUSQUEHANNA SES-ER-OL TABLE 1.1-3 1977 PROJECTION OF APPLICAN'A LOADS-CAPACITY-RESERVES (HIGH LOAD PROJECTION Year Winter Peak MWe 1978 4960 1979 5320 1980 5670 1981 6100 1982 6480 1983 6840 1984 7200 1985 7570 Capacity Changes Fossil (Oil)Nuclear Hydro Reratings 945(')945(l)63(2)Total Capacities Fossil (Coal)Fossil (Oil)CT 6 (j~sel Hydro Nuclear Firm Purchase Capacity Transactions 4145 1640 539 146 76 (41)4145 1640 539 146 76 (50)4145 1640 539 146 76 4145 1640 539 146 1890 76 4145 4145 4145 4145 1640 1640 1640 1640 539 539 539 539 146 146 146 209 945 1890 1890 1890 76 76 76 76 Total MWe 6505 6496 6436 7426 8405 8374 8343 8374 Reserve over winter peak: With Susquehanna MWe Capacity X of Load 1326 22 1925 30 1534 1143 22 16 804 ll Without Susquehanna MWe Capacity%of Load 1545 31 1176 22 766 14 326 5 (65)(436)(807)(1126)(1)(6)(ll)(15)With Susquehanna But Without Oil S Hydro Generation Without Susquehanna~
SUSQUEHANNA SES-ER-OL TABLE1.1-61977PROJECTION OFAPPLICAN'8 LOADS-CAPACITY-RESERVES (LOW-LOWLOADPROJECTION)
Oil 8 Hydro Generation Hwe Capacity (856)(1225)(17)(23)(1075)(476)(867)(1258)(1660)(18)(7)(13)(17)(22)(1635)(2075)(2466)(2837)(3208)(3590)(29)(34)(38)(41)(45)(47)Note: See Footnotes Following Table 1.1-6.
YearWinterPeakHWeCapacityChangesFossil(Oil)NuclearHydroReratings 19784530197945801980472019814890945(l)19825050945()19835230198454201985550063(2)TotalCapacities Fossil(Coal)Fossil(Oil)CT8(j~selHydroNuclearFixmPurchaseCapacityTransactions TotalHWe4145164053914676(41)65054145164053914676(50)64964145164053914676~llO6436(65)7426(31)8405(62)8374(93)8343(125)8374414541454145414541451640164016401640164053953953953953914614614614620994518901890189018907676767676Reserveoverwinterpeak:WithSusquehanna NWeCapacity$ofLoad253652335531442923666054287452WithoutSusquehanna MWeCapacitygofLoad1975441916421716153636311365271174229731894417WithSusquehanna ButWithoutOil6HydroGeneration MWeCapacitygofLoadWithoutSusquehanna, Oil6HydroGeneration (426)MWeCapacity(9)gofLoad1353(485)(685)(865)(11)(15)(18)9541974314(1036)(1227)(21)(23)522104107(1428)(1520)(26)(28)NOTE:SeeFootnotes Following Table1.1-6 SUSQUEHANNASES-ER-OL23.12.2Tornadoes Theincidence oftornadoes inthesiteareaisverylow.Betweentheyears1950and1973only38tornadoes werereportedwithin50milesofthesite.Tornadoactivityisatamaximumduringthesummermonthswithmosttornadoes occurring inthelateafternoon orevening.Figure2.3-1,TornadoOccurrence
SUSQUEHANNA SES"ER-OL TABLE 1.1-4 1977 PROJECTION OF APPLICAFA LOADS-CAPACITY-RESERVES MID-RANGE LOAD PROJECTION)
<<ndIntensity intheSusquehanna SZSReqion,isahistogram fortheyears1953-1962showingtornadofrequency bymonth,hourandintensity withina3by3~squarewhichiscenteredonthesite.Theintensity cateqories arebasedontheFujitatornadointensity classification (Ref.2.3-5).PromFigure2.3-1itcanbeseenthatmaximumtornadooccurrence isinthesummer.Diurnally, tornadofrequency reachesamaximumduringlateafternoon, shortlyaftertheperiodofgreatestinstability 23.1.23Th>>ndecstormsThunderstorms intheareaareusuallyofbriefdurationandconcentrated inthewarmmonths.Theyareresponsible focmostofthesummertime rainfallwhichnormallyavecaqesaround3.7inchespermonthatAvoca.Basedona19yearaverageatAvocathemeannumberof"dayswiththunderheard"is30(Ref2.3-3).Amonthlybreakdown ofthemeannumberofthunderstorm daysthatisrepresentative ofthesiteisshowninTable2.3-2,Thunderstocm DaysforAvoca.2.3.12.4L~ihtningThereisneitherdocumentation nordirectmeasurement oftheoccurrence oflightning otherthantheobservation ofassociated thunder.Localclimatological datatabulated bytheNationalWeatherService(Ref.2.3-3)doesnotprovideinformation reqardinq theincidence, severity.
Year Winter Peak MWe Capacity Changes Fossil (Oil)Nuclear Hydro Reratings 1978 4820 1979 5050 1980 5310 1981 5690 945(l)1982 5990 945"'983 6280 1984 6560 1985 6850 63(2)Total Capacities Fossil (Coal)Fossil (Oil)CT 6 (j~sel Hydro Nuclear Firm Purchase Capacity Transactions Total MWe 4145 1640 539 146 76 (41)6505 4145 1640 539 146 76 (50)6496 4145 1640 539 146 76~(110 6436 4145 1640 539 146 945 76 (65)7426 4145 1640 539 146 1890 76 (31)8405 4145 1640 539 146 1890 76 (62)8374 4145 1640 539 146 1890 76 4145 1640 539 209 1890 76~(93 (125)8343 8374 Reserve over winter peak: With Susquehanna MWe Capacity g of Load 1736 2415 31 40 2094 33 1783 1524'27 22 Without Susquehanna MWe Capacity$of Load 1685 1446 35 29 1126 21 736 13 425 7 124 2 (167)(406)(3)(6)With Susquehanna But Without Oil 6 Hydro Generation (665)(12)14 (307)(618)(940)1 (5)(9)(14)Without Susquehanna~
orfrequency oflightning occurrences A.thunderstocm canusuallybeheardunlesstheliqhtning causingthethunderismorethan15milesaway;therefore, thunderincidence canpresumably beusedtoconfirmthepresenceofsomelightning Thenumberoflightning strikespersquaremileperyearhasbeenestablished by,Uman(Ref.2.3-6).Thecombinedresultsofseveralstudiessummarized nyUmanindicatethatthenumberofflashestotheqroundpecsquaremileperyearisbetween005and0.80timesthenumberofthunderstorm dayspecyear.Themeannumberofdayswiththunderstorms probablyoverestimates theactualoccurrence ofcloud-to-ground lightning sincesomethunderstocms probablycontainonlycloud-to-cloud lightning.
Oil 6 Hydro Generation (716)(955)(1275)(1665)(1976)Mwe Capacity (15)(19)(24)(29)(33)NOTE: See Footnotes Following Table 1.1-6 (2277)(2568)(2870)(36), (39)(42)  
2~33 SUSQUEHANNA SES-ER-OLTherefore.
iftheannualthunderstorm frequency atAvocaisused(30days),thenumberof:groundlightning strikesisbetweentwoand24.23125HailHailinthesiteregionsometimes fallsfromseverethunderstorms.
Becausehailfallsinnarrowswaths,onlyasmallfractionofoccurrences isrecordedatregularreporting stationsTheaverageannualnumberofdayswithhailatapointintheareais23.Theoccurrence oflargehail(greaterthan0.75inchesdiameter) averaqesoneortwooccurrences annuallyAccordinq toPautz(Ref.2.3-7)thenumberofhailstorms withhail0.75inchorgreaterinaone-degree longitude-latitude squareareainthevicinityofthesitefortheperiod1955-1967 wasaboutfiveForAvocafrom1973-75therewasonehailstorm inJuneandoneinJulyof1973and1974.Xn1975therewasalsoonehailstorm inAugustandoneinOctoberTherewerenooccurrences ofhailrecordedin1976atAvoca(Ref.2.3-3)23.126ExtremeMindsStrongwindsoccurinPennsylvania asaresultofoccasional hurricanes, thunderstorms, tornadoes andtropicalstorms.Thefollowinq isthefastestmileofwindanditsassociated direction, bymonth,atAvoca(1955-1976)
(Ref.2.3-3).FastestMileofWindMonthmphDirection MonthmphDirection JanuaryFebruaryMarchAprilMayJune436049474043SEWSNWNWWJuly42NWAuqust50NESeptember 38SMOctober38ENovember45SDecember47SMThe50-yearand100-yearmeanfastestmilewindspeedsforthesiteareaare75milesperhourand80milesperhour,respectively (Ref.2.3-8).Accordinq toPautz,therewereeightwindstorms 50knotsandqreaterfortheonedegreelatitude-longitude squarethatincludestheSusquehanna SESfortheperiod1955-1967 (Ref.23-7).23-4 SUSQUEHANNA SES-ER-G'i.
TABLE2.3-33LONG-TERM TEMPERATURE (F)ATAVOCA(PeriodofRecord:1956-1974)
MonthJanuaryFebruaryMarchAprilJuneJulyAugustSeptember OctoberNovemberDecember33.518.435.344.758.970.019.327.238.047.879.083.056.861.380.759.273.652.163.048.836.142.232.822.0~DailMax~DailMiaMean26.027.336.048.558.967.972.270.062.952.640.829.167-10627889159327973410145944395308419771065ExtremeHicihestlowestAnnual58.939.849.4101Ref.2.3-3 SUSQUEHANNA SES-ER-OL TABLE2.3-49PRECIPITATION DATAFORAVOCA(PeriodofRecord:1956-1974)
MonthJanuaryFebruaryMarchAprilMayTotal(ininches)2.041.962.503.063.50Greatest24-Hour(ininches)1.521.602.201.592.58JuneJulyAugustSeptember OctoberNovemberDecember3.404.093.212.822.713.012.513.612.333.183.092.612.912.30Annual34.813.61Ref.2.3-3 SUSQUEHANNA SES-ER-OL.
TABLE2.3-81JOINTFREUENCY(%)OFWINDDIRECTION, WINDSPEEDANDSTABILITY FORAVOCA(PeriodofRecord:1971-1975)
Stability ClassBWindSpeed(kts)Se'ctorNNENEENEESESESSESSWSWWSWNWNNWTotal0-38989756544-6.1507.0548.05487-10.1164.0548.061642416758989911773.0137.0890.1507.2055.2877.0137.0205.0959.1507.21232118.2493.13011449.19181449.1986748.109665071.9726.1164.0890.10271.21921112.0411.0137768.0274.0342516.02050528.0274.006811-1617-21>21Total.3569.2071.1819.1660.1385.0721.0870.0698.2771.3364.4553~6773.6913.4531.3856.2871Relativefrequency ofoccurrences ofBStability
=4.8425Ref.2.3-4 SUSQUEHANNA SES-ER-OL SECTIONTITLEVOLUMEAPPENDICIESo orooooooeo~ooooooooorooroooooooooooIIIB1ANEVALUATION OFTHECOSTOFSERVICE.IMPACTOFADELAYINTHEIN-SERVICE DATESOFSUSQUEHANNA SES(JANUARY1978).......IIICURRENTLONG-RANGE FORECASTENERGYSALES6PEAKLOAD1976-1990.................
IIIB2APPLICANT' FORECASTING METHODOLOGY KWHSALESANDPEAKLOADSDECEMBER, 1976..IIINATIONWIDE FUELEMERGENCY RESPONSETOFPCORDERNO496.............
~IIISUSQUEHANNA RIVERWATERANALYSESSUMMARY...IIIEQUATIONS ANDASSUMPTIONS UTXLIZEDINTHECALCULATION OFINDIVIDUALANDPOPULATION DOSESTOMANoorooooo
~oreooeoooooooooor
~ooocoro~IIIENVIRONMENTAL TECHNICALSPECIFICATIONS...
~III Pit~PE'I SUSQUEHANNASES-ER-OLsite)andatDanville(about31miles(49.9km)downstream.
TheCorpsofEngineers hascompiledfloodstageanddischarge
.information fortheSusquehanna RiveratWilkes-Barre (Ref.2.4-7).Thesedataarebasedonrecordsoffloodstagesdatingfrom1991Dataforthefourmostseverefloodsofrecordarepresented inTable2.4-5,HistoricFloodsintheVicinityoftheSusquehanna SESTable2.4-5alsoincludesthestagesanddischarges forfloodsatthesiteandatDanville.
Thefloodfrequency characteristics oftheSusquehanna asmeasuredatDanvilleareillustrated inFigure2.4-6,FloodDischarge Frequency.
ThepassaqeofTropicalStormAgnesthrough.Pennsylvania onJune22and23,1972resultedinrecordfloodlevelsintheSusquehanna RiverBasinFloodcrestsexceededthepreviousrecordfloodlevel.of1936atWilkes-Barre by75feet(2.3m).AtDanville, alocalmaximumqaqelevelresulting froma1904icejamwasexceededby1.6feet(0.5m).Peakdischarqe atWilkes-Barrewasanestimated 345,000cfs(9,770m~/sec)oraunitdischarge of34.5cubicfeetpersecondpersguaremile(cfsm)(04m~/sec/km~)
.Accumulated runoffforthedrainageareaaboveWilkes-Barre fortheperiodof0000hours,June21,1972through2200hours,June27,1972totaled4.32inches(11.0cm)(Ref.24-13).24.25LowPlowsLongtermrecordsfromtheUSGSgagingstationsatDanvilleandWilkes-Barre providethedatabaseforthelowflewfrequencyanalysespresented inthisSubsection.
Longdurationlowflowfrequencyanalysishasbeenperformed bythePennsylvania Department ofEnvironmental Resources (DER).Theresulting curvesforlowf3.owdurations oftwoto60monthsandrecurrence intervals upto100yearsforDanvilleandWilkes-Barre areprovidedinFigures2.4-7,LowFlowDurationatDanvilleand2.4-8~LowFlowDurationatWilkes-Barre, respectively.
Tables2.4-6and2.4-7,Maqnitude andFrequency ofAnnualLowFlowoftheSusquehanna RiveratDanvilleandWilkes-Barre, Pa.respectively, discussthedischarge fordifferent recurrence intervals.
Tables2.4-8and2.4-9,DurationTableofDailyFlowoftheSusquehanna RiveratDanvilleandWilkes-Barre, Pa.respectively indicatetheriverdischarge (Ref.2.4-14).Themostextendeddroughtperiodoccurredinthe1960's.Thelowestconsecutive dayflowsforperiodsof183daysandlesshavealsooccurredinthisperiodThemeanmonthlyflowsatDanvilleandWilkes-Barre areprovidedinTable2.4-10a,MeanMonthlyDroughtYearFlowSequences.
MeanDailyFlowsDuring1964Drought,Table2.4-10bforthesetwostationsareprovidedforthefourlowestflowmonthsofthisyear24-5 SUSQUEHANNASES-ER-OLApolicydecision'oftheSusquehanna RiverBasinCommission reqardinq consumptive withdrawals duringlowflowperiodsprovidesthatnaturalflowsduringdroughtswillnothediminished byfuturewaterusers.OnSeptember 301976,thispolicydecisionwasimplemented asanAmendment to18CFRPart80'3(Susquehanna RiverBasinCommission, SubpartD-Standards forReview,Section803.61,Consumptive UsesofMater)(Ref.2.4-15).Compensation shallbereguiredforconsumptive usesofwaterduringperiodsoflowflow.Theprovisions ofthisregulation applytoconsumptive usesinitiated sinceJanuary23,19712426Sedimentation Annualsedimentyieldsinthereqionsurrounding thesitearespacially uniform.Neasurements atTowanda,Pa.about105miles(169km)abovethestation,indicateonannua'ediment yieldof150tons/sqmi(52.5metrictons/km~)
fromadrainaqeareaof7797sqmi(20,194km~).AnnualyieldsatDanville, 11,220sqmi(29,060km~)drainageareaareestimated tobe140tons/sqmi(49.0metrictons/km~)
(Ref24-8).Dailysedimentdischarges atindividual stationsarehighlyvariableThedailysedimentdischarqe atDanvilleranqesfromahighof556,000tons/day(504,400metrictons/day) toalowof18tons/day(16.3metrictons/day)
.Materqualitysamplinqatthesiteincludedmeasurement oftotalsuspended solidsArangeofvaluesfrom1.6mg/1to912.6mq/1withanaveraqevalueof57.0mg/1wasfound.TheseresultsarefurtherreportedinSubsection 2.43.Grainsizeanalysiswasperformed onwatersamplestakenin1974usinqanautomatic imageanalyzer.
Thegrainsizedetermination wasperformed ontreatedanduntreated riverwatersamples.Theresultsfortheuntreated samplesarereportedinTable24-11,SedimentGrainSizeDistribution.
2427MaterImpoundments TheSusquehanna Riversuppliesallthewaterrequiredfornormalstationoperation.
Aseven-acre (2.8ha.)spray'ond islocatedonsitetosupplywatertoemergency heatdissipation systems.Thewarmedwaterfromthereactorsiscooledviathepond'sspraysystemandthenrecirculated throuqhtheemergency coolingsystems.Thisspraypondhasarelatively impervious liner.Itisfree-forminshapetoconformtothenaturaltopography ofthearea.Embankments andditchesareprovidedtodirectsurfacewater2.4-6 SUS(}UEHANNA SES-ER-OL TABLE2.4-2MONTHLYAVERAGERIVERCONDITIONS STAGE,VEIOCITYANDDISCHARGE OCTOBERSTATION(RiverMile)~Sunbury(122.0)STAGEVELOCITYDIS(HARGE (Ft.msl)(Ft/sec)(Ft/sec)PresentProectedPresentProectedPresentProected420.9420.92.01.991648631Northumberland (123.5)Volverton Sta.(128.5)Danville(134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia(150.4)Berwick(159.1)Nescopeck (160.0)BeachHaven(162.4)Mapwallopen (163.9)PlantSite(165;5)Shickshinny (169.5)422.9427.8434.6447.9453.5457.4476.4477.6483.0483.3484.7487.9422.8427.6434.4447.7453.3'57.
2476.3477.4482.9483.1484.5487.70.83.01.81.61.01.61.91.61.51.02'0.73.31.81.61.01.51.01.91.51.40.92.75144512250834939474947494623462346234623459545704761474247074590440814408429042904290429042804270


SUS(}UEHANNA SES-ER-OL TABLE2.4-2(Continued)
SUS(UEHANNA SES-ER-OL TABLE 1.1-5 1977 PROJECTION OF APPLICANT LOADS-CAPACITY"RESERVES (IOW IOAD PROJECTION Year Winter Peak MWe Capacity Changes Fossil (Oil)Nuclear Hydro Reratings 1978 4650 1979 4720 1980 4910 1981 5170 945"'982 5390 945(" 1983 5650 1984 5920 1985 6050 63(2)Total Capacities Fossil (Coal)Fossil (Oil)CT 8 (j~sel Hydro Nuclear Firm Purchase Capacity Transactions Total Mwe 4145 1640 539 146 76 4145 1640 539 146 76 4145 1640 539 146 76 4145 1640 539 146 945 76 4145 4145 4145 1640 1640 1640 539 539 539 146 146 146 1890 1890 1890 76 76 76 6505 6496 6436 7426 8405 8374 8343 4145 1640 539 146 1890 76 (125)8374 Reserve over winter peak: With Susquehanna MWe Capacity~of Load 2256 3015 44 56 2724 48 2423 2324 41 38 Without Susquehanna MWe Capacity 4 of Load With Susquehanna But Without Oil 6 Hydro Generation MWe Capacity g of Load 1855 1776 1526 40 38 31 (145)(3)614 11 1256 1025 24 19 754 13 323 6 473 8 22 1 394 7 (140)(2)Without Susquehanna>
STATION(RiverMile)Sunbury(122.0)Northumberland (123.5)Wolverton Sta.(128.5)Danville(134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia(150.4)Berwick(159.1)Nescopeck (160.0)BeachHaven(162.4)Wapwallopen (163.9)PlantSite(165.5)Shickshinny (169.5)425.0429.8437.1451.2456.2460.0478.9479.8484.8485.5487.4490.8424.9429.7437.0451.1456.159.9478.8479.7484.8485.4487.3490.71.02.42.21.91.52.21.62.02.12.41.63.91.02.42.21.91.52.11.52.02'2.31.63.9124781209512457120771242112045120901174111648113071164811307113561102311356110231135611023113561102311291109761123210932STAGEVELOCITYDIS(HARGE (Ft.msl)(Ft/sec)(Ft/sec)PresentProectedPresentProectedPresentProected422.0421.93.43.42114620613 SUSQUEHANNA SES-ER-OL TABLE2.4-2(Continued)
Oil 8 Hydro Generation (546)(625)MWe Capacity (12)(13)g of Load NOTE: See Footnotes Following Table 1.1-6.(875)(1 145)(1376)(1647)(18)(22)(26)(29)(1928)(2070)(33)i (34)
STATION(RiverMile)STAGEVELOCITYDIS(HARGE (Ft.msl)(Ft/sec)(Pt/sec)PresentProectedPresentProectedPresentPro'ected Sunbury(122.0)Northumberland (123.5)Wolverton Sta.(128.5)Danville(134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia(150.4)Berwick(159.1)Nescopeck (160.0)BeachHaven(162')Wapwallopen (163.9)PlantSite(165.5)Shickshinny (169.5)426.2426.1431.0430.9438.5438.4453.2453.0457.5457.4461.4461.3480.2480.10481.1481.0485'485.7-486.7486.6488.8488.7492.4492.3422.6422.64.22.52.42.01.82.51.82.22.32.92.04.24.22.52.42.01.72.51.82.22.32.81.94.22984218028179581783517348166981669816270162701627016270161751608929309176451757817459169991635716357159371593715937159371586015789
SUSQUEHANNA SES-ER-OL TABLE 1.1-6 1977 PROJECTION OF APPLICAN'8 LOADS-CAPACITY-RESERVES (LOW-LOW LOAD PROJECTION)
Year Winter Peak HWe Capacity Changes Fossil (Oil)Nuclear Hydro Reratings 1978 4530 1979 4580 1980 4720 1981 4890 945(l)1982 5050 945()1983 5230 1984 5420 1985 5500 63(2)Total Capacities Fossil (Coal)Fossil (Oil)CT 8 (j~sel Hydro Nuclear Fixm Purchase Capacity Transactions Total HWe 4145 1640 539 146 76 (41)6505 4145 1640 539 146 76 (50)6496 4145 1640 539 146 76~llO 6436 (65)7426 (31)8405 (62)8374 (93)8343 (125)8374 4145 4145 4145 4145 4145 1640 1640 1640 1640 1640 539 539 539 539 539 146 146 146 146 209 945 1890 1890 1890 1890 76 76 76 76 76 Reserve over winter peak: With Susquehanna NWe Capacity$of Load 2536 52 3355 3144 2923 66 60 54 2874 52 Without Susquehanna MWe Capacity g of Load 1975 44 1916 42 1716 1536 36 31 1365 27 1174 22 973 18 944 17 With Susquehanna But Without Oil 6 Hydro Generation MWe Capacity g of Load Without Susquehanna, Oil 6 Hydro Generation (426)MWe Capacity (9)g of Load 135 3 (485)(685)(865)(11)(15)(18)954 19 743 14 (1036)(1227)(21)(23)522 10 410 7 (1428)(1520)(26)(28)NOTE: See Footnotes Following Table 1.1-6 S USQ UEH A N NA S ES-E R-OL 2 3.1 2.2 Tornadoes The incidence of tornadoes in the site area is very low.Between the years 1950 and 1973 only 38 tornadoes were reported within 50 miles of the site.Tornado activity is at a maximum during the summer months with most tornadoes occurring in the late afternoon or evening.Figure 2.3-1, Tornado Occurrence
<<nd Intensity in the Susquehanna SZS Reqion, is a histogram for the years 1953-1962 showing tornado frequency by month, hour and intensity within a 3 by 3~square which is centered on the site.The intensity cateqories are based on the Fujita tornado intensity classification (Ref.2.3-5).Prom Figure 2.3-1 it can be seen that maximum tornado occurrence is in the summer.Diurnally, tornado frequency reaches a maximum during late afternoon, shortly after the period of greatest instability 2 3.1.2 3 Th>>ndec storms Thunderstorms in the area are usually of brief duration and concentrated in the warm months.They are responsible foc most of the summertime rainfall which normally avecaqes around 3.7 inches per month at Avoca.Based on a 19 year average at Avoca the mean number of"days with thunder heard" is 30 (Ref 2.3-3).A monthly breakdown of the mean number of thunderstorm days that is representative of the site is shown in Table 2.3-2, Th understocm Days for Avoca.2.3.1 2.4 L~iht ning There is neither documentation nor direct measurement of the occurrence of lightning other than the observation of associated thunder.Local climatological data tabulated by the National Weather Service (Ref.2.3-3)does not provide information reqardinq the incidence, severity.or frequency of lightning occurrences A.thunderstocm can usually be heard unless the liqhtning causing the thunder is more than 15 miles away;therefore, thunder incidence can presumably be used to confirm the presence of some lightning The number of lightning strikes per square mile per year has been established by, Uman (Ref.2.3-6).The combined results of several studies summarized ny Uman indicate that the number of flashes to the qround pec square mile per year is between 0 05 and 0.80 times the number of thunderstorm days pec year.The mean number of days with thunderstorms probably over estimates the actual occurrence of cloud-to-ground lightning since some thunderstocms probably contain only cloud-to-cloud lightning.
2~3 3 SUSQUEHANNA S ES-ER-OL Therefore.
if the annual thunderstorm frequency at Avoca is used (30 days), the number of: ground lightning strikes is between two and 24.2 3 1 2 5 Hail Hail in the site region sometimes falls from severe thunderstorms.
Because hail f alls in narrow swa ths, only a small fraction of occurrences is recorded at regular reporting stations The average annual number of days with hail at a point in the area is 23.The occurrence of large hail (greater than 0.75 inches diameter)averaqes one or two occurrences annually Accordinq to Pautz (Ref.2.3-7)the number of hailstorms with hail 0.75 inch or greater in a one-degree longitude-latitude square area in the vicinity of the site for the period 1955-1967 was about five For Avoca from 1973-75 there was one hailstorm in June and one in July of 1973 and 1974.Xn 1975 there was also one hailstorm in August and one in October There were no occurrences of hail recorded in 1976 at Avoca (Ref.2.3-3)2 3.1 2 6 Extreme Minds Strong winds occur in Pennsylvania as a result of occasional hurricanes, thunderstorms, tornadoes and tropical storms.The followinq is the fastest mile of wind and its associated direction, by month, at Avoca (1955-1976)(Ref.2.3-3).Fastest Mile of Wind Month mph Direction Month mph Direction January February March April May June 43 60 49 47 40 43 SE W S NW NW W July 42 NW Auqust 50 NE September 38 SM October 38 E November 45 S December 47 SM The 50-year and 100-year mean fastest mile wind speeds for the site area are 75 miles per hour and 80 miles per hour, respectively (Ref.2.3-8).Accordinq to Pautz, there were eight windstorms 50 knots and qreater for the one degree latitude-longitude square that includes the Susquehanna SES for the period 1955-1967 (Ref.2 3-7).2 3-4 SUSQUEHANNA SES-ER-G'i.
TABLE 2.3-33 LONG-TERM TEMPERATURE (F)AT AVOCA (Period of Record: 1956-1974)
Month January February March April June July August September October November December 33.5 18.4 35.3 44.7 58.9 70.0 19.3 27.2 38.0 47.8 79.0 83.0 56.8 61.3 80.7 59.2 73.6 52.1 63.0 48.8 36.1 42.2 32.8 22.0~Dail Max~Dail Mia Mean 26.0 27.3 36.0 48.5 58.9 67.9 72.2 70.0 62.9 52.6 40.8 29.1 67-10 62 78 89 15 93 27 97 34 101 45 94 43 95 30 84 19 77 10 65 Extreme Hicihest lowest Annual 58.9 39.8 49.4 101 Ref.2.3-3 SUSQUEHANNA SES-ER-OL TABLE 2.3-49 PRECIPITATION DATA FOR AVOCA (Period of Record: 1956-1974)
Month January February March April May Total (in inches)2.04 1.96 2.50 3.06 3.50 Greatest 24-Hour (in inches)1.52 1.60 2.20 1.59 2.58 June July August September October November December 3.40 4.09 3.21 2.82 2.71 3.01 2.51 3.61 2.33 3.18 3.09 2.61 2.91 2.30 Annual 34.81 3.61 Ref.2.3-3 SUSQUEHANNA SES-ER-OL.
TABLE 2.3-81 JOINT FRE UENCY (%)OF WIND DIRECTION, WIND SPEED AND STABILITY FOR AVOCA (Period of Record: 1971-1975)
Stability Class B Wind Speed (kts)Se'ctor NNE NE ENE ESE SE SSE SSW SW WSW NW NNW Total 0-3 898 975 654 4-6.1507.0548.0548 7-10.1164.0548.0616 424 1675 898 991 1773.0137.0890.1507.2055.2877.0137.0205.0959.1507.2123 2118.2493.1301 1449.1918 1449.1986 748.1096 6507 1.9726.1164.0890.1027 1.2192 1112.0411.0137 768.0274.0342 516.0205 0 528.0274.0068 11-16 17-21>21 Total.3569.2071.1819.1660.1385.0721.0870.0698.2771.3364.4553~6773.6913.4531.3856.2871 Relative frequency of occurrences of B Stability=4.8425 Ref.2.3-4 SUSQUEHANNA SES-ER-OL SECTION TITLE VOLUME APPENDICIESo o r o o o o o o e o~o o o o o o o o o r o or o o o o o o o o o o o III B1 AN EVALUATION OF THE COST OF SERVICE.IMPACT OF A DELAY IN THE IN-SERVICE DATES OF SUSQUEHANNA SES (JANUARY 1978).......III CURRENT LONG-RANGE FORECAST ENERGY SALES 6 PEAK LOAD 1976-1990.................
III B2 APPLICANT' FORECASTING METHODOLOGY KWH SALES AND PEAK LOADS DECEMBER, 1976..III NATIONWIDE FUEL EMERGENCY RESPONSE TO FPC ORDER NO 496.............
~III SUSQUEHANNA RIVER WATER ANALYSES


SUSQUEHANNA SES-ER-OL TABLE2.4-2(Continued)
==SUMMARY==
STATION(RiverMile)STAGE(Ft.msl)PresentPro'ected VELOCITY(Ft/sec)PresentProectedDIS(HARGE (Ft/sec)PresentProectedSunbury(122.0)Northumberland (123.5)Volverton Sta.(128.5)Danville(134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia(150.4)Berwick(159.1)Nescopeck (160.0)BeachHaven(162.4)Mapwallopen (163.9)PlantSite(165.5)Shickshinny (169.5)425.6425.6430.4430.3437.7437.6452.0451.9456.7456.6460.6460.5479.5479.4480.4480.3485.2485.2486.0485.9488.0487.9491.5491.4422.3422.33.92.42.31.91.62.3-l.72.12.22.61.84.03.81.02.42.31.91.62.31.72.12.22.51.74.02585214978149081478514349137681376813384133841338413384132991322225319145951452814409140001342713427130511305113051130511298412922
...III EQUATIONS AND ASSUMPTIONS UTXLIZ ED IN THE CALCULATION OF IN DIVIDUAL AND POPULATION DOSESTOMANoorooooo
)0 SUSQUEHANNA SES-ER-OL TABLE2.4-2(Continued)
~or eooeoooooooooor
STATION(RiverMile)STAGE(Ft.msl)PresentProectedVELOCITY*(Ft/sec)PresentProectedDIS(HARGE (Ft/sec)PresentProectedSunbury(122.0)Northumberland (123.5)Wolverton Sta.(128.5)Danville(134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia(150.4)Berwick(159.1)Nescopeck (160.0)BeachHaven(162.4)Wapwallopen (163.9)PlantSite(165.5)Shickshinny (169.5)422.7426.2430.9438.3453.0457.5461.4480.1481.0485.8486.7488.7492.3422.6426.2430.8438.3452.9457.4461.3480.1481.0485.7486.6488.6492.24.32.52.42.01.82.51.82.22.32.81.94.24.32.52.42.01.82.51.82.12.32.81.94.21757617193174791709917308169321692016571166851634416685163441607115738160711573816071157381607115738158281551315759154593070430171 SUSQUEHANNA SES-ER-OL TABLE2.4-2(Continued)
~ooo coro~III ENVIRONMENTAL TECH NICA L S PECIFIC ATIONS...~III P i t~P E'I SUSQU EHANNA S ES-ER-OL site)and at Danville (about 31 miles (49.9 km)downstream.
STATION(RiverMile)STAGE(Ft.msl)PresentProectedVELOCITY(Ft/sec)PresentProectedDIS)HARGE (Ft/sec)PresentProectedSunbury(122.0)Northumberland (123.5)Wolverton Sta.(128.5)Danville(134.7)428.7428.7433.4433.4441.2441.1424.4424.45.61.32.72.85.61.32.72.85542031852317323152154887314693135231143Catawissa (143.7)Bloomsburg (146.6)Almedia(150.4)Berwick(159.1)Nescopeck (160.0)BeachHaven(164.2)Wapwallopen (163.9)PlantSite(165.5)Shickshinny (169.5)456.7460.4464.4482.9483.8488.0489.4491.9495.9456.7460.3464.4482.8483.7488.0489.4491.8495.92.42.33.12.52.62.93.82.75.02.42.33.12.52.62.93.82.75.0310653045830458300583005830058300582996929888307163011730117297252972529725297252965429588
The Corps of Engineers has compiled flood stage and discharge.information for the Susquehanna River at Wilkes-Barre (Ref.2.4-7).These data are based on records of flood stages dating from 1991 Data for the four most severe floods of record are presented in Table 2.4-5, Historic Floods in the Vicinity of the Susquehanna SES Table 2.4-5 also includes the stages and discharges f or floods at the site and at Danville.The flood frequency characteristics of the Susquehanna as measured at Danville are illustrated in Figure 2.4-6, Flood Discharge Frequency.
The passaqe of Tropical Storm Agnes through.Pennsylvania on June 22 and 23, 1972 resulted in record flood levels in the Susquehanna River Basin Flood crests exceeded the previous record flood level.of 1936 at Wilkes-Barre by 7 5 feet (2.3 m).At Danville, a local maximum qaqe level resulting from a 1904 ice jam was exceeded by 1.6 feet (0.5 m).Peak discharqe at Wilkes-Barre was an estimated 345,000 cfs (9,770 m~/sec)or a unit discharge of 34.5 cubic feet per second per sguare mile (cfsm)(0 4 m~/sec/km~)
.Accumulated runoff for the drainage area above Wilkes-Barre for the period of 0000 hours, June 21, 1972 through 2200 hours, June 27, 1972 totaled 4.32 inches (11.0 cm)(Ref.2 4-13).2 4.2 5 Low Plows Long term records from the USGS gaging stations at Danville and Wilkes-Barre provide the data base for the low flew f requency analyses presented in this Subsection.
Long duration low flow f requency analysis has been performed by the Pennsylvania Department of Environmental Resources (DER).The resulting curves for low f3.ow durations of two to 60 months and recurrence intervals up to 100 years for Danville and Wilkes-Barre are provided in Figures 2.4-7, Low Flow Duration at Danville and 2.4-8~Low Flow Duration at Wilkes-Barre, respectively.
Tables 2.4-6 and 2.4-7, Maqnitude and Frequency of Annual Low Flow of the Susquehanna River at Danville and Wilkes-Barre, Pa.respectively, discuss the discharge for different recurrence intervals.
Tables 2.4-8 and 2.4-9, Duration Table of Daily Flow of the Susquehanna River at Danville and Wilkes-Barre, Pa.respectively indicate the river discharge (Ref.2.4-14).The most extended drought period occurred in the 1960's.The lowest consecutive day flows for periods of 183 days and less have also occurred in this period The mean monthly flows at Danville and Wilkes-Barre are provided in Table 2.4-10a, Mean Monthly Drought Year Flow Sequences.
Mean Daily Flows During 1964 Drought, Table 2.4-10b for these two stations are provided for the four lowest flow months of this year 2 4-5 S USQ U EH A NNA S ES-E R-OL A policy decision'of the Susquehanna River Basin Commission reqardinq consumptive withdrawals during low flow periods provides that natural flows during droughts will not he diminished by future water users.On September 30 1976, this policy decision was implemented as an Amendment to 18 CFR Part 80'3 (Susquehanna River Basin Commission, Subpart D-Standards for Review, Section 803.61, Consumptive Uses of Mater)(Ref.2.4-15).Compensation shall be reguired for consumptive uses of water during periods of low flow.The provisions of this regulation apply to consumptive uses initiated since January 23, 1971 2 4 2 6 Sedimentation Annual sediment yields in the reqion surrounding the site are spacially uniform.Neasurements at Towanda, Pa.about 105 miles (169 km)above the station, indicate on annua'ediment yield of 150 tons/sq mi (52.5 metric tons/km~)from a drainaqe area of 7797 sq mi (20,194 km~).Annual yields at Danville, 11,220 sq mi (29,060 km~)drainage area are estimated to be 140 tons/sq mi (49.0 metric tons/km~)(Ref 2 4-8).Daily sediment discharges at individual stations are highly variable The daily sediment discharqe at Danville ranqes from a high of 556, 000 tons/day (504,400 metric tons/day)to a low of 18 tons/day (16.3 metric tons/day).Mater quality samplinq at the site included measurement of total suspended solids A range of values from 1.6 mg/1 to 912.6 mq/1 with an averaqe value of 57.0 mg/1 was found.These results are further reported in Subsection 2.4 3.Grain size analysis was performed on water samples taken in 1974 usinq an automatic image analyzer.The grain size determination was performed on treated and untreated river water samples.The results for the untreated samples are reported in Table 2 4-11, Sediment Grain Size Distribution.
2 4 2 7 Mater Impoundments The Susquehanna River supplies all the water required for normal station operation.
A seven-acre (2.8 ha.)spray'ond is located onsite to supply water to emergency heat dissipation systems.The warmed water from the reactors is cooled via the pond's spray system and then recirculated throuqh the emergency cooling systems.This spray pond has a relatively impervious liner.It is free-form in shape to conform to the natural topography of the area.Embankments and ditches are provided to direct surface water 2.4-6 SUS(}UEHANNA SES-ER-OL TABLE 2.4-2 MONTHLY AVERAGE RIVER CONDITIONS STAGE, VEIOCITY AND DISCHARGE OCTOBER STATION (River Mile)~Sunbury (122.0)STAGE VELOCITY DIS(HARGE (Ft.msl)(Ft/sec)(Ft/sec)Present Pro ected Present Pro ected Present Pro ected 420.9 420.9 2.0 1.9 9164 8631 Northumberland (123.5)Volverton Sta.(128.5)Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162.4)Mapwallopen (163.9)Plant Site (165;5)Shickshinny (169.5)422.9 427.8 434.6 447.9 453.5 457.4 476.4 477.6 483.0 483.3 484.7 487.9 422.8 427.6 434.4 447.7 453.3'57.2 476.3 477.4 482.9 483.1 484.5 487.7 0.8 3.0 1.8 1.6 1.0 1.6 1.9 1.6 1.5 1.0 2'0.7 3.3 1.8 1.6 1.0 1.5 1.0 1.9 1.5 1.4 0.9 2.7 5144 5122 5083 4939 4749 4749 4623 4623 4623 4623 4595 4570 4761 4742 4707 4590 4408 1 4408 4290 4290 4290 4290 4280 4270


SUSQUEHANNA SES-ER-OL TABLE2.4-2(Continued)
SUS(}UEHANNA SES-ER-OL TABLE 2.4-2 (Continued)
STATION(RiverMile)STAGE(Ft.msl)PresentProectedVELOCITY(Ft/sec)PresentProectedDIS(HARGE (Ft/sec)PresentProectedSunbury(122.0)Northumberland (123.5)Wolverton
STATION (River Mile)Sunbury (122.0)Northumberland (123.5)Wolverton Sta.(128.5)Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162.4)Wapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)425.0 429.8 437.1 451.2 456.2 460.0 478.9 479.8 484.8 485.5 487.4 490.8 424.9 429.7 437.0 451.1 456.1 59.9 478.8 479.7 484.8 485.4 487.3 490.7 1.0 2.4 2.2 1.9 1.5 2.2 1.6 2.0 2.1 2.4 1.6 3.9 1.0 2.4 2.2 1.9 1.5 2.1 1.5 2.0 2'2.3 1.6 3.9 12478 12095 12457 12077 12421 12045 12090 11741 11648 11307 11648 11307 11356 11023 11356 11023 11356 11023 11356 11023 11291 10976 11232 10932 STAGE VELOCITY DIS(HARGE (Ft.msl)(Ft/sec)(Ft/sec)Present Pro ected Present Pro ected Present Pro ected 422.0 421.9 3.4 3.4 21146 20613 SUSQUEHANNA SES-ER-OL TABLE 2.4-2 (Continued)
'Sta.(128')Danville(134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia(150.4)Berwick(159.1)Nescopeck (160.0)BeachHaven(162.4)Mapwallopen (163.9)PlantSite(165.5)Shickshinny (169.5)424.8429.2434.2442.1457.9461.3465.3483.6484.6488.7490.2492.8497.0424.7429.2434.2442.0457.8461;2465.3483.6484.6488.7490.2492.8496.95.85.91.41.437415370322.82.837256368762.92.936978366022.52.536331359822.52.535469351283.33-335469351282.72.734900345672.72.734900345673.03.034900345674.14.134900345672.92.934774344595.35.334659343596135460821 0
STATION (River Mile)STAGE VELOCITY DIS(HARGE (Ft.msl)(Ft/sec)(Pt/sec)Present Pro ected Present Pro ected Present Pro'ected Sunbury (122.0)Northumberland (123.5)Wolverton Sta.(128.5)Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162')Wapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)426.2 426.1 431.0 430.9 438.5 438.4 453.2 453.0 457.5 457.4 461.4 461.3 480.2 480.10 481.1 481.0 485'485.7-486.7 486.6 488.8 488.7 492.4 492.3 422.6 422.6 4.2 2.5 2.4 2.0 1.8 2.5 1.8 2.2 2.3 2.9 2.0 4.2 4.2 2.5 2.4 2.0 1.7 2.5 1.8 2.2 2.3 2.8 1.9 4.2 29842 18028 17958 17835 17348 16698 16698 16270 16270 16270 16270 16175 16089 29309 17645 17578 17459 16999 16357 16357 15937 15937 15937 15937 15860 15789
STATION(RiverMile)SUSQUEHANNA SES-ER-OL TABLE2.4-2(Continued)
STAGEVELOCITY(Ft.msl)(Ft/sec)PresentProectedPresentProectedDIS(HARGE (Ft/sec)PresentProectedSunbury(122.0)Northumberland (123.5)Wolverton Sta.(128.5)Danville(134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia(150.4)Berwick(159.1)Nescopeck (160.0)BeachHaven(162.4)Wapwallopen (163.9)PlantSite(165.5)Shickshinny (169.5)423.0426.7431.3438.7453.5457.8461.7480.4481.4486.0487.0489.1492.8423.0426.7431.2438.7453.4457.7461.7480.4481.3486.0486.9489.0492.74.62.52.42.01.82.61.92.22.43.02.04.34.52.52.42.01.82.51.92.22.42.92.04'350153488219326189431922918849190601868418567.1821817909175681790917568174751714217475171421745717142174751714217379170641729116991 SUSQUEHANNA SES-ER-OL TABLE2.4-2(Continued)
STATION()(RiverMile)Sunbury(122.0)Northumberland (123.5)Wolverton Sta.(128.5)Danville(134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia(150.4)Berwick(159.1)Nescopeck (160.0)BeachHaven(162.4)Wapwallopen (163.9)PlantSite(165.5)Shickshinny (169.5)424.8424;7429.5429.4436.7436.6450.6450.5455.7455.6459.5459.447.8.5478.3479.4484.5479.3484.5485.1485.0486.9486.8490.3490.2STAGE(Ft.msl)PresentProected421.8421.83.43.30.90.92.42.42.22.11.81.81.41.42.12.01.51.42.02.0~2.02.02.22.21.51.53.83.7VELOCITY(Ft/sec)PresentPro'ected1110810725110541067410959105831063810289102119870102119870993095979930959799309597993095979868955398119511DIS(HARGE (Ft/sec)PresentProected1991519382 SUS(}UEHANNA SES-ER-OI TABLE2.4-2(Continued)
STATION(RiverMile)STAGE(Ft.msl)PresentProectedVELOCITY(Ft/sec)PresentProectedDIS(HARGE (Zt/sec)PresentProectedSunbury(122.0)Northumberland (123.5)Volverton Sta.(128.5)Danville(134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia(150.4)Berwick(159.1)Nescopeck (160.0)BeachHaven(162.4)Mapwallopen (163.9)PlantSite(165.5)Shickshinny (169.5)421.0423.0427.8434.7448.0453.6457.5476.6477.7483.2483.5484.9488.1420.9422.9427.7434.5447.8453.4457.3476.4.477.5483.0483.3484.7487.92.00.73.01.81.61.61.91.61.51.02.92.00.73.21.81.61.01.61.91.61.41.02.852774894524748675194481851164767501246715012467149444611494446114944461149444611492946144915461597349201


SUS(}UEHANNA SES-ER-OL TABLE2.4-2(Continued)
SUSQUEHANNA SES-ER-OL TABLE 2.4-2 (Continued)
STATION()(RiverMile)STAGE(Ft.msl)PresentProectedVELOCI1Y(Ft/sec)PresentProectedDIS(HARGE (Ft/sec)PresentProectedSunbury(122.0)Northumberland (123.5)Wolverton Sta.(128.5)Danville(134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia(150.4)Berwick(159.1)Nescopeck (160.0)BeachHaven(162.4)Wapwallopen (163.9)PlantSite(165.5)Shickshinny (169.5)422.2422.1427.2427.1433.8433.6446.7446.2452.5452.2456.5.456.3475.6475.5476.7476.5482.2482.0482.4482.2483.6483.4487.5487.1420.6420.51.50.74.41.71.70.91.30.92.11.41.20.82.01.50.64.21.61.90.91.30.8,2.31.30.71.965203480346034253278308230822953295329532953292428985987309730803049292927412741262026202620262026202598 STATION(RiverMile)SUSQUEHANNA SES-ER-OL TABLE2.4-2(Continued)
STATION (River Mile)STAGE (Ft.msl)Present Pro'ected VELOCITY (Ft/sec)Present Pro ected DIS(HARGE (Ft/sec)Present Pro ected Sunbury (122.0)Northumberland (123.5)Volverton Sta.(128.5)Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162.4)Mapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)425.6 425.6 430.4 430.3 437.7 437.6 452.0 451.9 456.7 456.6 460.6 460.5 479.5 479.4 480.4 480.3 485.2 485.2 486.0 485.9 488.0 487.9 491.5 491.4 422.3 422.3 3.9 2.4 2.3 1.9 1.6 2.3-l.7 2.1 2.2 2.6 1.8 4.0 3.8 1.0 2.4 2.3 1.9 1.6 2.3 1.7 2.1 2.2 2.5 1.7 4.0 25852 14978 14908 14785 14349 13768 13768 13384 13384 13384 13384 13299 13222 25319 14595 14528 14409 14000 13427 13427 13051 13051 13051 13051 12984 12922
STAGEVELOCITY(Ft.msl)(Ft/sec)PresentProectedPresentProectedDIS(HARGE (Ft/sec)PresentProectedSunbury(122.O)Northumberland (123.5)Wolverton Sta.(128.5)Danville(134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia(150.4)Berwick(159.1)Nescopeck (160.0)BeachHaven(162.4)Wapwallopen (163.9)PlantSite(165.5)Shickshinny (169.5)42o.6422.2427.2433.8446.9452.5456.6475.7476.8482.2482.4483.7487.5420.5422.0427.2433.'6446.3452.3456.4475.5476.6482.1482.2483.5487.11.40.74.41.71.60.91.30.92.11.41.20.82.01.40.74.31.71.90.91.30.82.21.40.72.035823199356831883543316733833034317028293170282929532620303026973030269730302697299926842971267161375604 SUS(}UEHANNA SES-ER-OL TABLE2.4-2(Continued)
)0 SUSQUEHANNA SES-ER-OL TABLE 2.4-2 (Continued)
Stationlocations areindicated asthenearestmunicipality orfeaturetotherivercross-section usedinthecomputations.
STATION (River Mile)STAGE (Ft.msl)Present Pro ected VELOCITY*(Ft/sec)Present Pro ected DIS(HARGE (Ft/sec)Present Pro ected Sunbury (122.0)Northumberland (123.5)Wolverton Sta.(128.5)Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162.4)Wapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)422.7 426.2 430.9 438.3 453.0 457.5 461.4 480.1 481.0 485.8 486.7 488.7 492.3 422.6 426.2 430.8 438.3 452.9 457.4 461.3 480.1 481.0 485.7 486.6 488.6 492.2 4.3 2.5 2.4 2.0 1.8 2.5 1.8 2.2 2.3 2.8 1.9 4.2 4.3 2.5 2.4 2.0 1.8 2.5 1.8 2.1 2.3 2.8 1.9 4.2 17576 17193 17479 17099 17308 16932 16920 16571 16685 16344 16685 16344 16071 15738 16071 15738 16071 15738 16071 15738 15828 15513 15759 15459 30704 30171 SUSQUEHANNA SES-ER-OL TABLE 2.4-2 (Continued)
Theexactcross-section locationisindicated byrivermile.OneFoot=0.3048meterOneFootPerSecond=0.3048meterpersecondOneCubicFootPerSecond=0.0283cubicmeterspersecond.
STATION (River Mile)STAGE (Ft.msl)Present Pro ected VELOCITY (Ft/sec)Present Pro ected DIS)HARGE (Ft/sec)Present Pro ected Sunbury (122.0)Northumberland (123.5)Wolverton Sta.(128.5)Danville (134.7)428.7 428.7 433.4 433.4 441.2 441.1 424.4 424.4 5.6 1.3 2.7 2.8 5.6 1.3 2.7 2.8 55420 31852 31732 31521 54887 31469 31352 31143 Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (164.2)Wapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)456.7 460.4 464.4 482.9 483.8 488.0 489.4 491.9 495.9 456.7 460.3 464.4 482.8 483.7 488.0 489.4 491.8 495.9 2.4 2.3 3.1 2.5 2.6 2.9 3.8 2.7 5.0 2.4 2.3 3.1 2.5 2.6 2.9 3.8 2.7 5.0 31065 30458 30458 30058 30058 30058 30058 29969 29888 30716 30117 30117 29725 29725 29725 29725 29654 29588
SUSQUEHANNA SES-ER-OL TABLE2.4"3MONTHLYPERCENTCHANCEOFFLOODINGSUSUEHANNARIVERUPSTREAMOFSUNBURYMonthJanPercentChanceofFloodin6.8FebMarAprMayJunJulAugSeptOctNovDec7.540.419.08.22,12.11.41.03.42.75.4(1)Sunburyis43miles(69km)downstream ofthesiteattheconfluence oftheSusquehanna RiverandtheWestBranchSusquehanna River.
 
SUSQUEHANNA SES-ER-OL SECTIONTITLEVOLUMEAPPENDXCIESeesssseoeos~ee~eeeessssssss~seses~seIIIB1ANEVALUATION OFTHECOSTOFSERVICEIMPACTOFADELAYINTHEIN-SERVICE DATESOFSUSQUEHANNA SES(JANUARY1978).....IIICURRENTLONG-RANGE FORECASTENERGYSALESPEAKLOAD1976-1990......................III B2APPLICANT' FORECASTING NETHODOLOGY KMHSALESANDPEAKLOADSDECEMBER, 1976...IIINATXONMIDEFUELEilERGENCYRESPONSETOFPCORDERNO496....................
SUSQUEHANNA SES-ER-OL TABLE 2.4-2 (Continued)
~IIISUSQUEHANNA RIVERMATERANALYSESSUNHARY..IIIEQUATIONS ANDASSUMPTIONS UTXLIZEDINTHECALCULATION OFINDIVIDUAL ANDPOPULATION DOSESTOMAN....IIIENVIRONMENTAL TECHNICAL SPECIFICATIONS-
STATION (River Mile)STAGE (Ft.msl)Present Pro ected VELOCITY (Ft/sec)Present Pro ected DIS(HARGE (Ft/sec)Present Pro ected Sunbury (122.0)Northumberland (123.5)Wolverton'Sta.(128')Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162.4)Mapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)424.8 429.2 434.2 442.1 457.9 461.3 465.3 483.6 484.6 488.7 490.2 492.8 497.0 424.7 429.2 434.2 442.0 457.8 461;2 465.3 483.6 484.6 488.7 490.2 492.8 496.9 5.8 5.9 1.4 1.4 37415 37032 2.8 2.8 37256 36876 2.9 2.9 36978 36602 2.5 2.5 36331 35982 2.5 2.5 35469 35128 3.3 3-3 35469 35128 2.7 2.7 34900 34567 2.7 2.7 34900 34567 3.0 3.0 34900 34567 4.1 4.1 34900 34567 2.9 2.9 34774 34459 5.3 5.3 34659 34359 61354 60821 0
-III SUSgUEHAxfHASESEROLAccuracy1%fullscaleCurrentfull-scale deflection Inputimpedence ResponseTime'RritingTypeChartSpeedChannels1.0milliampere s1400ohms0.5secondsCurvilinear 3in/hour1oneachchart2charts/recorder Allrecording devices,translator=
STATION (River Mile)SUSQUEHANNA SES-ER-OL TABLE 2.4-2 (Continued)
andthedigitizer arehousedinaweatherproof cinderblock building.
STAGE VELOCITY (Ft.msl)(Ft/sec)Present Pro ected Present Pro ected DIS(HARGE (Ft/sec)Present Pro ected Sunbury (122.0)Northumberland (123.5)Wolverton Sta.(128.5)Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162.4)Wapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)423.0 426.7 431.3 438.7 453.5 457.8 461.7 480.4 481.4 486.0 487.0 489.1 492.8 423.0 426.7 431.2 438.7 453.4 457.7 461.7 480.4 481.3 486.0 486.9 489.0 492.7 4.6 2.5 2.4 2.0 1.8 2.6 1.9 2.2 2.4 3.0 2.0 4.3 4.5 2.5 2.4 2.0 1.8 2.5 1.9 2.2 2.4 2.9 2.0 4'35015 34882 19326 18943 19229 18849 19060 18684 18567.18218 17909 17568 17909 17568 17475 17142 17475 17142 17457 17142 17475 17142 17379 17064 17291 16991 SUSQUEHANNA SES-ER-OL TABLE 2.4-2 (Continued)
Thisbuildinghasthermistatically controlled heatingandairconditioning.
STATION()(River Mile)S unbury (122.0)Northumberland (123.5)Wolverton Sta.(128.5)Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162.4)Wapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)424.8 424;7 429.5 429.4 436.7 436.6 450.6 450.5 455.7 455.6 459.5 459.4 47.8.5 478.3 479.4 484.5 479.3 484.5 485.1 485.0 486.9 486.8 490.3 490.2 STAGE (Ft.msl)Present Pro ected 421.8 421.8 3.4 3.3 0.9 0.9 2.4 2.4 2.2 2.1 1.8 1.8 1.4 1.4 2.1 2.0 1.5 1.4 2.0 2.0~2.0 2.0 2.2 2.2 1.5 1.5 3.8 3.7 VELOCITY (Ft/sec)Present Pro'ected 11108 10725 11054 10674 10959 10583 10638 10289 10211 9870 10211 9870 9930 9597 9930 9597 9930 9597 9930 9597 9868 9553 9811 9511 DIS(HARGE (Ft/sec)Present Pro ected 19915 19382 SUS(}UEHANNA SES-ER-OI TABLE 2.4-2 (Continued)
6..1.3.1.15Calibration andYaintenance oftheSystemAllcalibration andmaintenance ispeformedatleastsemi-annuallyinaccordance withthefrequencies andproducedures prescribed inthemanufacturer's operating andmaintenance manual.61.3.1.1.6 DataAnalysisTheanalogchartrecordsareremovedevery14daysforinspection andanalysis.
STATION (River Mile)STAGE (Ft.msl)Present Pro ected VELOCITY (Ft/sec)Present Pro ected DIS(HARGE (Zt/sec)Present Pro ected Sunbury (122.0)Northumberland (123.5)Volverton Sta.(128.5)Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162.4)Mapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)421.0 423.0 427.8 434.7 448.0 453.6 457.5 476.6 477.7 483.2 483.5 484.9 488.1 420.9 422.9 427.7 434.5 447.8 453.4 457.3 476.4.477.5 483.0 483.3 484.7 487.9 2.0 0.7 3.0 1.8 1.6 1.6 1.9 1.6 1.5 1.0 2.9 2.0 0.7 3.2 1.8 1.6 1.0 1.6 1.9 1.6 1.4 1.0 2.8 5277 4894 5247 4867 5194 4818 5116 4767 5012 4671 5012 4671 4944 4611 4944 4611 4944 4611 4944 4611 4929 4614 4915 4615 9734 9201
Eachchartisremovedseparately andplacedinindividual boxeslabeledwithdate,instrument'nd level.Thechartsareinspected forbreaksinrecord,timeerrors,powerfailuresandotherindications ofsystemmalfunction andthenstored.Theinformation gainedfromthisinspection isusedtoupdateandverifythedigitaldata,andtolocateanomalies withanyparameter.
 
Theanalogrecording systemprovidesaback-upincaseofdigitalsystemfailure,sothatahighdatarecoveryratecanbemaintained.
SUS(}UEHANNA SES-ER-OL TABLE 2.4-2 (Continued)
Table6.1-2,DataRecoveryBates,givestherecoveryratesforeachyear.Digitalminutedataarerecordedatthesiteonmagneictapeforanalysis.
STATION()(River Mile)STAGE (Ft.msl)Present Pro ected VELOCI1Y (Ft/sec)Present Pro ected DIS(HARGE (Ft/sec)Present Pro ected Sunbury (122.0)Northumberland (123.5)Wolverton Sta.(128.5)Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162.4)Wapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)422.2 422.1 427.2 427.1 433.8 433.6 446.7 446.2 452.5 452.2 456.5.456.3 475.6 475.5 476.7 476.5 482.2 482.0 482.4 482.2 483.6 483.4 487.5 487.1 420.6 420.5 1.5 0.7 4.4 1.7 1.7 0.9 1.3 0.9 2.1 1.4 1.2 0.8 2.0 1.5 0.6 4.2 1.6 1.9 0.9 1.3 0.8, 2.3 1.3 0.7 1.9 6520 3480 3460 3425 3278 3082 3082 2953 2953 2953 2953 2924 2898 5987 3097 3080 3049 2929 2741 2741 2620 2620 2620 2620 2620 2598 STATION (River Mile)SUSQUEHANNA SES-ER-OL TABLE 2.4-2 (Continued)
Atthebegi.nning ofeachscanofdataauniqueidentification code,thedate,'hour andminuteisrecorded.
STAGE VELOCITY (Ft.msl)(Ft/sec)Present Pro ected Present Pro ected DIS(HARGE (Ft/sec)Present Pro ected Sunbury (122.O)Northumberland (123.5)Wolverton Sta.(128.5)Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162.4)Wapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)42o.6 422.2 427.2 433.8 446.9 452.5 456.6 475.7 476.8 482.2 482.4 483.7 487.5 420.5 422.0 427.2 433.'6 446.3 452.3 456.4 475.5 476.6 482.1 482.2 483.5 487.1 1.4 0.7 4.4 1.7 1.6 0.9 1.3 0.9 2.1 1.4 1.2 0.8 2.0 1.4 0.7 4.3 1.7 1.9 0.9 1.3 0.8 2.2 1.4 0.7 2.0 3582 3199 3568 3188 3543 3167 3383 3034 3170 2829 3170 2829 2953 2620 3030 2697 3030 2697 3030 2697 2999 2684 2971 2671 6137 5604 SUS(}UEHANNA SES-ER-OL TABLE 2.4-2 (Continued)
After14daysofrecording, thetapeisremoved,labeledwiththedataperiodandforwarded totheApplicant, Thecomputer6.1-13 SUSQUEHANNA SES-ER-OL/facilityprocesses thesetapesconverting therecordedmillivoltaqes intoenqineerinq units.Anhourlyaveraqeforeachparameter iscomputedDatavalidity, rangeofhourlyaveragesandthenumberofvalidobservations contributinq totheaveragesaretabulated toassistinthedetermination ofdatareliability.
Station locations are indicated as the nearest municipality or feature to the river cross-section used in the computations.
Comparisons betweentheanaloganddiqitaldataareperformed whenthebi-weekly reviewofthedigitaldatarevealsqu'estionable orinvaliddata.Temperature anddewpointhourlyaveragesarecomputedusingthefollowinqscalarequation:
The exact cross-section location is indicated by river mile.One Foot=0.3048 meter One Foot Per Second=0.3048 meter per second One Cubic Foot Per Second=0.0283 cubic meters per second.
B.=1Zr.B..n.jjii=1where:theaveragehourlyvalueforthejthvariable(inphysicalunits);B..thetotalnumberofminuteobservations duringthehour(normally 60),butifnislessthan15forthathour,dataareconsidered tobemissing;thei"minuteobservation onthe3+"variable(millivolts):
SUSQUEHANNA SES-ER-OL TABLE 2.4"3 MONTHLY PERCENT CHANCE OF FLOODING SUS UEHANNA RIVER UPSTREAM OF SUNBURY Month Jan Percent Chance of Floodin 6.8 Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec 7.5 40.4 19.0 8.2 2,1 2.1 1.4 1.0 3.4 2.7 5.4 (1)Sunbury is 43 miles (69 km)downstream of the site at the confluence of the Susquehanna River and the West Branch Susquehanna River.
theconversion factortochangethej<hvariable frommillivolts intophysicalunits.Afterwindspeed(WS)andwinddirection (WD)areconverted frommillivolts theyarerelatedinthefollowinq manner:IfWSisinvalid(999)thenWDismarkedinvalid(999)andviceversa.IfWS)threshold (non-calm) andWD=0(implying calm)thenWDissetto360~(North)IfWS(threshold (calm)andWD)0(implying non-calm) thenWDissetto0o(calm)Hourlyaveragesarecomputedasscalarsforwindspeed.Winddirection averagesare,determined asfollows:Iftheassociated averaqewindspeedisgreaterthan1.34112meters/sec, (3mph),averageWDisdetermined byvectoranalysis(whereWSandWDforeachminutedetermines avector).61-14 SUSQUEHANNASES-ER-OLAPPENDIXB2APPLICANT~S PORECASTING METHODOLOGY KMHSALESANDPEAKLOADSDecember, 1976 INTRODUCTION ThePP&Lenergymodelforecasts KWHconsumption foreachofthemajorgroupsinthePP&LServiceArea;i.e.,oRESIDENTIAL oCOMMERCIAL oINDUSTRIAL oRESALE,STREETLIGHTINGANDRAILROADAneconometric modelisdeveloped byconsidering thedeterminants foreachofthesectors.Whilethemodel,bynecessity, isasimplification, itcapturesthecruciallinkagesbetweensectoractivityandKWHsales,providing theuserwithastructural framework forforecasting.
SUSQUEHANNA SES-ER-OL SECTION TITLE VOLUME APP EN DXCIESe e s s s s e o e o s~e e~e e e e s s s s s s s s~s e s e s~s e I I I B1 AN EVALUATION OF THE COST OF SERVICE IMPACT OF A DELAY IN THE IN-SERVICE DATES OF SUSQUEHANNA SES (JANUARY 1 978).....III CURRENT LONG-RANGE FORECAST ENERGY SALES PEAK LOAD 1976-1990......................III B2 APPLICANT' FORECASTING NETHODOLOGY KMH SALES AND PEAK LOADS DECEMBER, 1976...III NATXON MIDE FU EL EilER GE NCY RES PON SE TO FPC OR DER NO 496....................
Throughthemodelausercanproduceaforecastofsalesforeachofthesectorsconsistent withaneconomicoutlook.Moreimportantly theimpactofalternative economicscenarios canbetested.Inarrivingataforecast, themodelutilizesinformation andforecasts oftheU.S.economy,thenationalenergymarket,theCentralEasternPennsylvania (C.E.P.)economy,localweatherconditions andcompanypolicy.Thisinformation isobtainedfromacombination ofexistingforecasting servicesandreviewswithPP&LEnergyConsultants.
~III SUSQUEHANNA RIVER MATER ANALYSES SUNHARY..III EQUATIONS AND ASSUMPTIONS UTXLIZ ED IN THE CALCULATION OF INDIVIDUAL AND POPULATION DOS ES TO MAN....III ENVIRONMENTAL TECHNICAL SPECIFICATIONS-
ThePP&Lmodelbuildsfromthatpoint,measuring theimpactofthenationaleconomicoutlookontheC.E.P.region.Thisoutlookisthencombinedwithassumptions aboutweatherconditions andcompanypolicytoproduceaforecastofenergysalestoeachofthesectors.MODELSTRUCTURE Indeveloping amodelofelectricenergyconsumption foraparticular regionitisimportant to,Qrst,definethedemandconditions presentinthatservicearea,andsecond,measuretheirimpactonsalestoeachofthesectors.ThePP&Lenergymodelisdeveloped withinthistwo-stage process.Inthefirststageofthemodel,demandconditions aredefined,i.e.,climaticconditions, theeconomicenvironment, energyprices,andcompanypolicy.Weather,energy'costs andcompanypolicyareallexogenous inputstothemodel.Theeconomicconditions aredeveloped endogenously throughan'conometric frame-work.Thesecondstagemeasurestheimpactofthesedemandconditions oneachsectorthroughasetofeconometric equations, relatingsalestothosefactorsthatareknowntoaffectgrowth.Thegeneralflowofthemodelisgiven.inFigureI.
-III SUSg UEHAxfH A SES ER OL Accuracy 1%f u ll scale Current full-scale deflection Input impedence Respon se Time'Rriting Type Chart Speed Channels 1.0 milliampere s 1400 ohms 0.5 seconds Curvilinear 3 in/hour 1 on each chart 2 charts/recorder All recording devices, translator=
TheserviceareaeconomicmodelislinkedtotheDRIMacroEconomicModel,bridgingthegapbetweenthenationaleconomyandlocalsalesbyhighlighting regionalcharacteristics (i.e.,industrial mix,growthtrends,demographic mix,etc.)andbyincluding explicitly theimpactofthenationaleconomyontheregion.Thislinkageisprimarily throughtheindustrial sector.Forexample,thesteelindustryintheC.E.P.regionservesanationalmarket,therefore, theirsalesdependondemandconditions inthenation.Indeveloping amodeltoforecastthegrowthofthesteelindustryintheregionitisnecessary toincludenationaleconomy.Asanotherex-ample,thehousingindustryintheareaisheavilydependent onlocalwealthanddemographic mix,butadepressed steelindustrywouldlowerlocalwealththerebyslowinghousinggrowth.Thefunctionoftheserviceareamodelistoliterthesenationalconditions soastomeasuretheirimpactonthelocaleconomy.Thus,theelectricuseforecastisdeveloped inthefollowing way.Afore-castofthenationaleconomy,developed throughtheDRIMacroModel,isacceptedoralteredtoreflectPP&L.'sthinking.
and the digitizer are housed in a weatherproof cinderblock building.This building has thermistatically controlled heating and air conditioning.
ThatforecastisfQteredthroughtheserviceareaeconomicmodeltodetermine localeconomicconditions.
6..1.3.1.1 5 Calibration and Yaintenance of the System All calibration and maintenance is pe formed at least semi-annually in accordance with the frequencies and producedures prescribed in the manufacturer's operating and maintenance manual.6 1.3.1.1.6 Data Analysis The analog chart records are removed every 14 days for inspection and analysis.Each chart is removed separately and placed in individual boxes labeled with date, instrument'nd level.The charts are inspected for breaks in record, time errors, power failures and other indications of system malfunction and then stored.The information gained from this inspection is used to update and verify the digital data, and to locate anomalies with any parameter.
Againtheuserhastheoptionofaccepting theresultsoralteringthemwherehedeemsnecessary.
The analog recording system provides a back-up in case of digital system failure, so that a high data recovery rate can be maintained.
Theeconomics arecombinedwithassumptions aboutenergyprices,expectedweatherconditions andcompanypolicytodefinethelocaldemandconditions.
Table 6.1-2, Data Recovery Bates, gives the recovery rates for each year.Digital minute data are recorded at the site on magne ic tape for analysis.At the begi.nning of each scan of data a unique identification code, the date,'hour and minute is recorded.After 14 days of recording, the tape is removed, labeled with the data period and forwarded to the Applicant, The computer 6.1-13 SUSQUEHANNA S ES-ER-OL/facility processes these tapes converting the recorded millivoltaqes into enqineerinq units.An hourly averaqe for each parameter is computed Data validity, range of hourly averages and the number of valid observations contributinq to the averages are tabulated to assist in the determination of data reliability.
Finally,thisinformation determines theexpectedlevelofmegawatthour sales.Ateachstagetheforecaster hastheabilitytoadjusttheoutputofthemodelbeforegoingon.ItallowstheusertherequiredQexibility tomakethemodelausefultool.Thenextthreesectionsdetailthemethodology usedindeveloping theeconomicandenergymodels.SERVICEAREAECONOMICMODELTheCentralEasternPennsylvania (C.E.P.)economicmodelisconstructed tohighlight theregionaleconomywithinthePP&Lservicearea.Itprovidesinfor-mationaboutfourmajoreconomicareas:A.INDUSTRIAL SECTORB.COMMERCIAL SECTORC.WAGES&PERSONALINCOME.D.HOUSINGThegeneralQowofthemodelisdepictedinFigureII.Briefly,themodelunfoldsasfollows.Theindustrial sector,throughemployment, islinkedtothenationaleconomy.Thetightness ofthelocallabormarket,alongwithinflationary conditions, determine thelevelofmanufacturing wages.Inthenextstage,employ-mentinthecommercial sectorandpercapitapersonalincomearesimultaneously determined; theirlevelsaredependent onindustrial activityandareinterdependent witheachother.Finally,population ofthehouse-owning agegroupiscombinedwithlocalwealthandemployment conditions, andnationalinformation ontheQnancialmarketstodetermine thehousingmarketgrowth.Abriefdescription ofeachareafollows.0 A.INDUSTRIAL SECTORAregion'smanufacturing sector,primarily itsexporting industries, providethemajorlinkbetweenthenationalandregionaleconomies.
Comparisons between the analog and diqital data are performed when the bi-weekly review of the digital data reveals qu'estionable or invalid data.Temperature and dew point hourly averages are computed using the f ollowinq scalar equation: B.=1 Z r.B..n.j ji i=1 where: the average hourly value for the jth variable (in physical units);B..the total number of minute observations during the hour (normally 60), but if n is less than 15 f or that hour, data are considered to be missing;the i" minute observation on the 3+" variable (millivolts):
Thus,wewouldexpectthissectortofollowthenationalpatternsgiventhatitservesanationalmarket.However,weexpectthelocalindustries tomaintainregionalcharacteristics aswell,fromthestandpoint oflocational decisions onthepartofentering/exiting manufacturing
the conversion factor to change the j<hvariable from millivolts into physical units.After wind speed (WS)and wind direction (WD)are converted from millivolts they are related in the followinq manner: If WS is invalid (999)then WD is marked invalid (999)and vice versa.If WS)threshold (non-calm) and WD=0 (implying calm)then WD is set to 360~(North)If WS (threshold (calm)and WD)0 (implying non-calm)then WD is set to 0o (calm)Hourly averages are computed as scalars for wind speed.Wind direction averages are, determined as follows: If the associated averaqe wind speed is greater than 1.34112 meters/sec, (3 mph), average WD is determined by vector analysis (where WS and WD for each minute determines a vector).6 1-14 S USQU EH A NNA S ES-ER-OL APPENDIX B2 APPLICANT~S PORECASTING METHODOLOGY KMH SALES AND PEAK LOADS December, 1976 INTRODUCTION The PP&L energy model forecasts KWH consumption for each of the major groups in the PP&L Service Area;i.e., o RESIDENTIAL o COMMERCIAL o INDUSTRIAL o RESALE, STREET LIGHTING AND RAILROAD An econometric model is developed by considering the determinants for each of the sectors.While the model, by necessity, is a simplification, it captures the crucial linkages between sector activity and KWH sales, providing the user with a structural framework for forecasting.
: concerns, Inmodelling manu-facturing employment inthePP&Lserviceareaeveryattemptwasmadetoincludethesetwoaspects:linkagewiththenationaleconomyandregionallocational decisions
Through the model a user can produce a forecast of sales for each of the sectors consistent with an economic outlook.More importantly the impact of alternative economic scenarios can be tested.In arriving at a forecast, the model utilizes information and forecasts of the U.S.economy, the national energy market, the Central Eastern Pennsylvania (C.E.P.)economy, local weather conditions and company policy.This information is obtained from a combination of existing forecasting services and reviews with PP&L Energy Consultants.
.B.COMMERCIAL SECTORThetypeofservicesprovidedandproductssoldwithinthecommercial sectorarequitesimilaracrossdifferent regionsofthecountry.However,thegrowthofthissectorwithinaregionisheavilydependent uponthelocaleconomy.Indeveloping thecommercial employment equations, thegrowthineachofthesesectorswascomparedtotheirbreakdowns nationally.
The PP&L model builds from that point, measuring the impact of the national economic outlook on the C.E.P.region.This outlook is then combined with assumptions about weather conditions and company policy to produce a forecast of energy sales to each of the sectors.MODEL STRUCTURE In developing a model of electric energy consumption for a particular region it is important to, Qrst, define the demand conditions present in that service area, and second, measure their impact on sales to each of the sectors.The PP&L energy model is developed within this two-stage process.In the first stage of the model, demand conditions are defined, i.e., climatic conditions, the economic environment, energy prices, and company policy.Weather, energy'costs and company policy are all exogenous inputs to the model.The economic conditions are developed endogenously through an'conometric frame-work.The second stage measures the impact of these demand conditions on each sector through a set of econometric equations, relating sales to those factors that are known to affect growth.The general flow of the model is given.in Figure I.
TherelativegrowthoftheareawasthencomparedtotherelativeU.S.growthinpopulation andpercapitaincome.C.WAGES,PRICES,ANDPERSONALINCOMEManufacturing averagehourlyearningsandtotalpersonalincomefortheserviceareaareforecasted withintheC.E.P.economicmodel,buildingfromtheemployment situation inthemanufacturing andcommercial sectors.Inaddition, aforecastoflocalinflation conditions isdeveloped directlyfromtheinflation conditions ofthenation.D.HOUSINGSECTORThegrowthinthehousingstockisanimportant determinant ofresidential sales.Therefore, intheeconomicmodel,weexplictly modelhousehold formations intheservicearea.Indeveloping thissectorwehaveachoiceoftwoavailable dataseries,household permitsfromthefederalgovernment andnewdwellingunitstatistics fromPPaLrecords.Thedwellingunitdata,considered morereliableandeasiertomonitor,wasused.Thelong-rundemandforhousingishypothesized tobea'unction ofthepopulation ofthehouse-owning agegroupandthelevelofhousehold wealth.IV.RESIDENTIAL SECTORTheresidential modelhasbeendeveloped toforecastsalestothetwomajorclassesofresidential service;viz.,electrically heatedhomesandgeneralresidential.
The service area economic model is linked to the DRI Macro Economic Model, bridging the gap between the national economy and local sales by highlighting regional characteristics (i.e., industrial mix, growth trends, demographic mix, etc.)and by including explicitly the impact of the national economy on the region.This linkage is primarily through the industrial sector.For example, the steel industry in the C.E.P.region serves a national market, therefore, their sales depend on demand conditions in the nation.In developing a model to forecast the growth of the steel industry in the region it is necessary to include national economy.As another ex-ample, the housing industry in the area is heavily dependent on local wealth and demographic mix, but a depressed steel industry would lower local wealth thereby slowing housing growth.The function of the service area model is to liter these national conditions so as to measure their impact on the local economy.Thus, the electric use forecast is developed in the following way.A fore-cast of the national economy, developed through the DRI Macro Model, is accepted or altered to reflect PP&L.'s thinking.That forecast is fQtered through the service area economic model to determine local economic conditions.
Indoingsothemodelisdividedintotwoblocks:oCUSTOMERBLOCKoUSAGEBLOCK Inthecustomerblockthenumber.ofresidential customers undereachoftheservicesisdetermined.
Again the user has the option of accepting the results or altering them where he deems necessary.
The'usage blockdetermines theaveragekWhusagepercustomerundereachofthe,services.
The economics are combined with assumptions about energy prices, expected weather conditions and company policy to define the local demand conditions.
Totalresidential usageisobtainedbysummingtheproductofcustomerstockandpercustomerusageineachofthegroups.CustomerBlockTotalresidential customers inanyperiodisequaltothenumberinthepreviousperiod,plusthenewunitscomingon,lessthedepreciation oftheexistingstock.Inestimating ourusagepercustomerequations, theimpactofthefollowing determinants wasmeasured.
Finally, this information determines the expected level of megawatthour sales.At each stage the forecaster has the ability to adjust the output of the model before going on.It allows the user the required Qexibility to make the model a useful tool.The next three sections detail the methodology used in developing the economic and energy models.SERVICE AREA ECONOMIC MODEL The Central Eastern Pennsylvania (C.E.P.)economic model is constructed to highlight the regional economy within the PP&L service area.It provides infor-mation about four major economic areas: A.INDUSTRIAL SECTOR B.COMMERCIAL SECTOR C.WAGES&PERSONAL INCOME.D.HOUS ING The general Qow of the model is depicted in Figure II.Briefly, the model unfolds as follows.The industrial sector, through employment, is linked to the national economy.The tightness of the local labor market, along with inflationary conditions, determine the level of manufacturing wages.In the next stage, employ-ment in the commercial sector and per capita personal income are simultaneously determined; their levels are dependent on industrial activity and are interdependent with each other.Finally, population of the house-owning age group is combined with local wealth and employment conditions, and national information on the Qnancial markets to determine the housing market growth.A brief description of each area follows.0 A.INDUSTRIAL SECTOR A region's manufacturing sector, primarily its exporting industries, provide the major link between the national and regional economies.
oHOUSEHOLD INCOMEoPRICEOFELECTRICITY oPEOPLEPERHOUSEHOLD oWEATHERCONDITIONS oCONSERVATION EFFORTSV.FigureIIIshowstherelationships thatareconsidered inmodelling thissector.COMMERCIAL SECTORTheCommercial Sectorpresentsadifficult modelling tasktotheforecaster.
Thus, we would expect this sector to follow the national patterns given that it serves a national market.However, we expect the local industries to maintain regional characteristics as well, from the standpoint of locational decisions on the part of entering/exiting manufacturing concerns, In modelling manu-facturing employment in the PP&L service area every attempt was made to include these two aspects: linkage with the national economy and regional locational decisions.B.COMMERCIAL SECTOR The type of services provided and products sold within the commercial sector are quite similar across different regions of the country.However, the growth of this sector within a region is heavily dependent upon the local economy.In developing the commercial employment equations, the growth in each of these sectors was compared to their breakdowns nationally.
Overthepast10to15yearsithasshownsteadygrowth,becominganincreasing portionoftotalsales;yetlittleinformation isavailable overthisintervalonthetypeofloadserved.Thebestthatcanbedoneinlieuofcommercial surveysandexpandeddatacollection istoincludein,themodelthoseeconomicindicators thatbestdepictthegrowthofthesecustomers.
The relative growth of the area was then compared to the relative U.S.growth in population and per capita income.C.WAGES, PRICES, AND PERSONAL INCOME Manufacturing average hourly earnings and total personal income for the service area are forecasted within the C.E.P.economic model, building from the employment situation in the manufacturing and commercial sectors.In addition, a forecast of local inflation conditions is developed directly from the inflation conditions of the nation.D.HOUSING SECTOR The growth in the housing stock is an important determinant of residential sales.Therefore, in the economic model, we explictly model household formations in the service area.In developing this sector we have a choice of two available data series, household permits from the federal government and new dwelling unit statistics from PPaL records.The dwelling unit data, considered more reliable and easier to monitor, was used.The long-run demand for housing is hypothesized to be a'unction of the population of the house-owning age group and the level of household wealth.IV.RESIDENTIAL SECTOR The residential model has been developed to forecast sales to the two major classes of residential service;viz., electrically heated homes and general residential.
Themodelling taskisnotoneofobtaining satisfactory summarystatistics, theycomerathereasily,butrathertobesurethattherealdeterminants andindicators ofgrowthareinthe'model.
In doing so the model is divided into two blocks: o CUSTOMER BLOCK o USAGE BLOCK In the customer block the number.of residential customers under each of the services is determined.
Inadditiontotheoverallgrowth,thepriceofelectricity, weatherconditions andconservation areconsidered important determinants ofsalesandareincluded.
The'usage block determines the average kWh usage per customer under each of the, services.Total residential usage is obtained by summing the product of customer stock and per customer usage in each of the groups.Customer Block Total residential customers in any period is equal to the number in the previous period, plus the new units coming on, less the depreciation of the existing stock.In estimating our usage per customer equations, the impact of the following determinants was measured.o HOUSEHOLD INCOME o PRICE OF ELECTRICITY o PEOPLE PER HOUSEHOLD o WEATHER CONDITIONS o CONSERVATION EFFORTS V.Figure III shows the relationships that are considered in modelling this sector.COMMERCIAL SECTOR The Commercial Sector presents a difficult modelling task to the forecaster.
Salestothecommercial sectorarecollected byfourmajorclasses:oWholesale andRetailTradeoFinancial andPersonalServicesoOtherCommercial oSmallCommercial Thegeneraloutlineofestimating thissectorisexhibited inFigureIV.
Over the past 10 to 15 years it has shown steady growth, becoming an increasing portion of total sales;yet little information is available over this interval on the type of load served.The best that can be done in lieu of commercial surveys and expanded data collection is to include in, the model those economic indicators that best depict the growth of these customers.
INDUSTRIAL SECTORTheIndustrial Modelwasdeveloped toforecastKWHsalestofourteenmajorindustrial classes.Thesalesforecastfortheindustrial sectoris'theaggregation ofthesefourteencia'sses, thebreakdown ofwhichisgiveninthetablebelowandtheflowdiagram.shownasExhibitV.INDUSTRIAL SECTORBREAKDOWN OFINDUSTRIAL CLASSESSICINDUSTRY202223272832433(less331)331353611512Food&KindredProductsTextileMillProductsApparelPrinting&Publishing Chemicals
The modelling task is not one of obtaining satisfactory summary statistics, they come rather easily, but rather to be sure that the real determinants and indicators of growth are in the'model.
&AlliedProductsCementPrimaryMetals(exceptSteel)SteelManufacturing Non-Electrical Machinery Electrical Riachinery OtherMetalProducts>
In addition to the overall growth, the price of electricity, weather conditions and conservation are considered important determinants of sales and are included.Sales to the commercial sector are collected by four major classes: o Wholesale and Retail Trade o Financial and Personal Services o Other Commercial o Small Commercial The general outline of estimating this sector is exhibited in Figure IV.
OtherGeneralIndustry2 SmallIndustrial CoalMiningNote:l.IncludesMining(SIC10),Ordnance(SIC19),Fabricated Metals(SIC34),Transportation Equipment (SIC37)andInstruments (SIC38).2.IncludesOilaGasExtractions (SIC13),MiningaQuarrying (SIC14),TobaccoProducts(SIC21),LumberandWoodProducts(SIC24),Furniture andFixtures(SIC25),PaperandAlliedProducts(SIC26),Petroleum Refining(SIC29),RubberandPlastics(SIC30),LeatherandProducts(SIC31),Stone,ClayandGlass,lessCement(SIC32.less324),Miscellaneous Industries (SIC39).Intheindustrial model,fourmajorfactorswereconsidered:
INDUSTRIAL SECTOR The Industrial Model was developed to forecast KWH sales to fourteen major industrial classes.The sales forecast for the industrial sector is'the aggregation of these fourteen cia'sses, the breakdown of which is given in the table below and the flow diagram.shown as Exhibit V.INDUSTRIAL SECTOR BREAKDOWN OF INDUSTRIAL CLASSES SIC INDUSTRY 20 22 23 27 28 324 33 (less 331)331 35 36 11512 Food&Kindred Products Textile Mill Products Apparel Printing&Publishing Chemicals&Allied Products Cement Primary Metals (except Steel)Steel Manufacturing Non-Electrical Machinery Electrical Riachinery Other Metal Products>Other General Industry2 S mall Industrial Coal Mining Note: l.Includes Mining (SIC 10), Ordnance (SIC 19), Fabricated Metals (SIC 34), Transportation Equipment (SIC 37)and Instruments (SIC 38).2.Includes Oil a Gas Extractions (SIC 13), Mining a Quarrying (SIC 14), Tobacco Products (SIC 21), Lumber and Wood Products (SIC 24), Furniture and Fixtures (SIC 25), Paper and Allied Products (SIC 26), Petroleum Refining (SIC 29), Rubber and Plastics (SIC 30), Leather and Products (SIC 31), Stone, Clay and Glass, less Cement (SIC 32.less 324), Miscellaneous Industries (SIC 39).In the industrial model, four major factors were considered:
oProduction ActivityoFactorSubstitution oTechnological ChangeoConservation VII.SUMMARYInsummary,thePP5LEconometric Modelforecasts th'eshortandlong-term kWhconsumption forthemajorconsuming sectors,inthe.PPaLServiceArea.Itutilizesforecasts fromtheDRIMacroModeltogetherwithregionaleconomic, demo-graphic,andclimaticconditions-to determine ascenariooftheserviceareaeconomy.Assumptions aboutthepriceofelectricity andcompeting fuels,weatherexpectations, theworkingagepopulation, andtechnological changesarethenmade,fromwhichpointthemodelproducesakWhforecast.
o Production Activity o Factor Substitution o Technological Change o Conservation VII.
OutlooksarealsopreparedbyPPaLEnergyConsultants.
 
Intheresidential sector,themodelforecasts kWhsalesforElectrically HeatedHomesandGeneralResidential Service.Forbothoftheseclasses,salesistheproductofthenumberofcustomers andusageper.customer.
==SUMMARY==
Thenumberofcustomers isafunctionofemployment intheservicearea,realdisposable income,newdwellingunits,thepriceofelectricity andcompeting fuels,andnewmortgagecommitments.
In summary, the PP5L Econometric Model forecasts th'e short and long-term kWh consumption for the major consuming sectors, in the.PPaL Service Area.It utilizes forecasts from the DRI Macro Model togetherwith regional economic, demo-graphic, and climatic conditions-to determine a scenario of the service area economy.Assumptions about the price of electricity and competing fuels, weather expectations, the working age population, and technological changes are then made, from which point the model produces a kWh forecast.Outlooks are also prepared by PPaL Energy Consultants.
Usagepercustomerisdetermined, forthemostpart,bytherealpriceofelectricity, realdisposable income,andweather.Themodel,whichdevelopsthemathematical relationships amongthesevariables, thenfore-castsresidential sales.Commercial sales,whicharesegregated intofourcategories, areafunctionofcommercial employment intheservicearea,realdisposable income,therealpriceofelectricity, andweather.Thegrowthincommercial demandispositively relatedtothefirsttwovariables whilenegatively relatedtothethird.Bysolvingaseriesofequations, themodel'determines thekWhconsumption inthecommercial sector.Theforecastofindustrial salesmakesuseofestimates ofindustrial output,whichinturnisafunctionofmanufacturing employment.
In the residential sector, the model forecasts kWh sales for Electrically Heated Homes and General Residential Service.For both of these classes, sales is the product of the number of customers and usage per.customer.
Manufacturing employment, bytwo-digit SICCodesinthePPaLserviceareadependsuponcurrentlevelsofemployment andthelevelofproduction foraparticular industry.
The number of customers is a function of employment in the service area, real disposable income, new dwelling units, the price of electricity and competing fuels, and new mortgage commitments.
Industrial outputinourserviceareaisdefinedastheFederalReserveBoardProduction IndextimestheratioofPPSLemployment toU~S.employment.
Usage per customer is determined, for the most part, by the real price of electricity, real disposable income, and weather.The model, which develops the mathematical relationships among these variables, then fore-casts residential sales.Commercial sales, which are segregated into four categories, are a function of commercial employment in the service area, real disposable income, the real price of electricity, and weather.The growth in commercial demand is positively related to the first two variables while negatively related to the third.By solving a series of equations, the model'determines the kWh consumption in the commercial sector.The forecast of industrial sales makes use of estimates of industrial output, which in turn is a function of manufacturing employment.
Salestothefourteenindustrial SICgroupsaremainlydetermined byfindingtherelationship ofkWhsalestoserviceareaindustrial output,therelativepriceofelectricity tofueloil,therelativepriceofelectricity tonaturalgas,andanytechnological changesthatmightoccur.Nomodel,regardless ofhowwellitisspecified, willforecastperfectly.
Manufacturing employment, by two-digit SIC Codes in the PPaL service area depends upon current levels of employment and the level of production for a particular industry.Industrial output in our service area is defined as the Federal Reserve Board Production Index times the ratio of PPSL employment to U~S.employment.
Therewillbeexogenous events,suchaslargenewloadsorchangesincompanyorgovernment policy,thatthemodelisunabletopickup.Inthesecases,theresultsofthemodelcanbemodifiedtothedesiredlevelbyjudgment.
Sales to the fourteen industrial SIC groups are mainly determined by finding the relationship of kWh sales to service area industrial output, the relative price of electricity to fuel oil, the relative price of electricity to natural gas, and any technological changes that might occur.No model, regardless of how well it is specified, will forecast perfectly.
VIII.PEAKLOADFORECASTInordertoadequately provideforourcustomers'emands forelectricity, adequategenerating capacitymustbeavailable.
There will be exogenous events, such as large new loads or changes in company or government policy, that the model is unable to pick up.In these cases, the results of the model can be modified to the desired level by judgment.VIII.PEAK LOAD FORECAST In order to adequately provide for our customers'emands for electricity, adequate generating capacity must be available.
Theamountofcapacityrequiredisdetermined byforecasting summerandwintersystempeakloadsfortentofifteenyearsintothefuture.Summerandwintersystempeaksareforecasted becauseitisduringtheseperiodsthatthegreatestdemandsaremadeonoursystem.Airconditioning loadcausesthesummerpeaks,andlightingandspaceheatingloadsareresponsible forthoseinthewinter.
The amount of capacity required is determined by forecasting summer and winter system peak loads for ten to fifteen years into the future.Summer and winter system peaks are forecasted because it is during these periods that the greatest demands are made on our system.Air conditioning load causes the summer peaks, and lighting and space heating loads are responsible for those in the winter.
PPEL'sestimating procedure producessummerandwintersystempeakloadsbydeveloping thecontribution madebyeachrateclass.Theterm"rateclass"meansallcustomers servedundersimilarrateschedules.
PPEL's estimating procedure produces summer and winter system peak loads by developing the contribution made by each rate class.The term"rate class" means all customers served under similar rate schedules.
Thesaleofenergyforecastdeveloped byrevenueclassesisreallocated torateclassesusingobservedhistorical relationships.
The sale of energy forecast developed by revenue classes is reallocated to rate classes using observed historical relationships.
Loadstudydataisthenbroughtintotheestimation process.Ourloadstudiesaredesignedtodetermine theloadcharacteristics ofaspecificclassofservice.Whenmetersareofthewatt-hour type,stratified randomsamplesofcustomers withinkilowatt-hour rangesareused.Inthecaseofmostgeneralservicesamplecustomers (upto7000kwwithdemandmeterbilling),
Load study data is then brought into the estimation process.Our load studies are designed to determine the load characteristics of a specific class of service.When meters are of the watt-hour type, stratified random samples of customers within kilowatt-hour ranges are used.In the case of most general service sample customers (up to 7000 kw with demand meter billing), load factor ranges within each rate class are used.Larger commercial and industrial customers are studied individually.
loadfactorrangeswithineachrateclassareused.Largercommercial andindustrial customers arestudiedindividually.
Daily load curves for the days of summer and winter system peak are derived for every stratum of each rate class for an average customer.For customers studied by kilowatt-hour ranges, demand per customer data for each stratum of each rate class are multiplied by the number of customers in the universe of that stratum to obtain a universe daily load curve.The number of customers in a stratum is obtained from the Company's bill frequency distributions.
Dailyloadcurvesforthedaysofsummerandwintersystempeakarederivedforeverystratumofeachrateclassforanaveragecustomer.
This can also be done for years other than the load study test year because the load characteristics of a kWh or load factor stratum remain fairly constant with only the number of customers in a stratum changing from year to year.Daily load curves for load factor stratum are stated as ratios of customer monthly maximum demand.These are applied to the sum of customer demands in each load factor stratum as determined from an hours-use distribution to obtain the universe daily load curve.For an historical year the strata of a given rate class are added together to form the daily load curve for the universe of that rate class.The rate class load curves for the days of summer and winter system peak of a given year are corrected for losses to the net generation level and added together to form the summer and winter load curves for the system.The result is checked against actual peak loads.Using these techniques we have developed rate class contributions to summer and winter system peaks historically for selected hours of the day.The ratio between class contribution to system peak and annual sales to that class is calculated for each rate class at the time of summer and winter system peak, for every historical period analyzed.The trend of this ratio for either a summer or a winter syst'm peak is fairly constant over time.For a given class the trend of this ratio for the time of both summer and winter system peak is projected through time.By applying the appropriate ratios to the predicted annual sales of any future year, that class'ontribution to summer and winter peak is forecasted.
Forcustomers studiedbykilowatt-hour ranges,demandpercustomerdataforeachstratumofeachrateclassaremultiplied bythenumberofcustomers intheuniverseofthatstratumtoobtainauniversedailyloadcurve.Thenumberofcustomers inastratumisobtainedfromtheCompany's billfrequency distributions.
The system peak for a specific time period is obtained by adding together the projected class contributions to system peak.
Thiscanalsobedoneforyearsotherthantheloadstudytestyearbecausetheloadcharacteristics ofakWhorloadfactorstratumremainfairlyconstantwithonlythenumberofcustomers inastratumchangingfromyeartoyear.Dailyloadcurvesforloadfactorstratumarestatedasratiosofcustomermonthlymaximumdemand.Theseareappliedtothesumofcustomerdemandsineachloadfactorstratumasdetermined fromanhours-use distribution toobtaintheuniversedailyloadcurve.Foranhistorical yearthestrataofagivenrateclassareaddedtogethertoformthedailyloadcurvefortheuniverseofthatrateclass.Therateclassloadcurvesforthedaysofsummerandwintersystempeakofagivenyeararecorrected forlossestothenetgeneration levelandaddedtogethertoformthesummerandwinterloadcurvesforthesystem.Theresultischeckedagainstactualpeakloads.Usingthesetechniques wehavedeveloped rateclasscontributions tosummerandwintersystempeakshistorically forselectedhoursoftheday.Theratiobetweenclasscontribution tosystempeakandannualsalestothatclassiscalculated foreachrateclassatthetimeofsummerandwintersystempeak,foreveryhistorical periodanalyzed.
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etlFL(t(t(KAl i~ca~~1(7Th(EHrl(telD41 SQvCE~.peaurerPRgNAIIH~~ICCWCCPgakoPOOVmITO(LI~~.IlAgtVl((M~5@V~rCEA~I'Sr'(lar.
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OCO~ttIdH~PP PAILEL, CXBRK PvL<<H~Kv u.S.(~~3~v)r LP ITS~~I L 3 I PRa<>~W~I I SCRI CE H2CA HWH PdlDTIM&+PCS'~HIS+NalH'k@HIQKLS t ALLIS)PQg)~~H4H~CvHB T he%)PAC.TCILIW I PRIcz cF~&cb~CC r I Pha CP~~I 55bJ I C v I~H'g-I"~~ACTCC.i~IIIdH pIIIITACV I-EIpL5 (, 5;s,~3 C%EL~'P CcCCC,5 HulH~~+ICAL r~luEAV CA r~lmm II43H crHalL cm~~immi keAN~ImIHl5iiL~
~~OldRLQK~~ICE1II(e(1(~CIocoaee~vsIIIrFQt(l0MIIJ6CC"~QTIAI+~MT'~AIL ILCLIIL,~RRBORATlhr5~O(eKRVATLON (ILIigureIII RrvezAav~vQR'IMACROMOOEIorU.S.ECOMOtf!IIIQQSMIAL
t C Q$5NATICN I I IN cvsnu~c Bmoc IIIiIH CCRC.NISI~TOTAL~WAW HO@%.SALES IMDV5TTRIAL ScCTA Exhibit V SUSQU EH ANNA SES-ER-OL contaminated by airborne radioiodine is a potential source of exposure.Samples from milk animals are considered a better indicator of radioiodine in the environment than vegetation.
~ItnAL~~~T.(TWO0&TQAMQCWAI)
If the census reveals milk animals are not present or are unavailable for sampling, then veqetation may be sampled.The 500-sq.ft.garden, considering 20%used for growing green leafy vegetables and a vegetation yield of 2 kg/m>will produce the 26 kq/yr assumed in~Re ula~tor Guide 1.109 (March 1974)for child consumption of leaf y veqetation.
~gERVlCKAX~A'M~PelcaS'~ICSPagAISGhnCEPCXA-NONABACICIAJVlAL,WPlghfllCAIT'SCbnCt~>>r~~~~APL~CATSERuCC,A~i~CCC4CC~POPULUSTIClH~~~.ll~VlIImCChl45AREA.~u~Ka5,~~'Saeva~IEH~~'usus~+aeAlt'T$4DC'5$2llCEAQUA.N'AH~PllOKWACLESWC~WP4a~CEHDLCthHCIJTRIIAIICIAI PER&~~~CCl4bVAlPllgth PIP~'.AI4PtQ,~~le%HAHCOu~mOlltKP~EQ.CIAIIptICKcP~C~C~IL9+Rs~~o~I(@AMER.C&L "DECTCR.HwHICOIJIItT~IItHE&hk)A,T lICIIQ.CDt1HFQC;Al cE~~RIIIr~SeWWIII ll40lhMIAL SECtCA.~TIDAL.EW~mur(~Ol&TSMAKQOWL))
The option to consider the garden to be at the nearest residence is conservative and those locations may be used to calculate doses due to radioactive ef fluent releases in place of the actual locations which would be determined by the census.The permission of deviations from the sampling schedule is based on the recognition of unavoidable practical difficulties which in the absence of the permitted deviations would result in violation of the specifications.
~5ERVICEAIL'QXKS~PILICI.S'QRVIC3PC@AIPueOuu-I~EIglgACCICV~aKRncaALKA.~m~mr'SEbnCE~v~PCR~IN~~~~+IPCPVIAr&NI~~-Ileal(gagLIIIQCpQUOITSeahICACTA.vam'55blICI'.
The requirement for the participation in the EPA cross-check program, or similar program, is based on the need for independent checks on the precision and accuracy of the measurements of radioactive material in environmental monitorinq in order to demonstrate the validity of the results.~Re oeting Requirement A.Annual Environmental Operatinq Report, Part B, Radiological.
Adrh-P4CL5aRIAI.5CILVICvi hREA(~O<CgTCQEACOul)
A report on the radiological environmental sur veillance proqram for the previous calender year shall be submitted to the Director of the NRC Regional Office (with a copy to the Director, Office of Nuclear Reactor Requlation) as a separate document in May of each year.The period of the first report shall begin with the date of initial criticality The report shall include a.summary (format of Table F-1, Environmental Monitoring Program Summary)interpretations, and statistical evaluation of the results of the radiological environmental surveillance activities for the report period, includinq a comparison with operational, controls, preoperational studies (as appropriate) and previous environmental surveillance reports and an assessment of the observed impacts of the station operation on the environment.
P7gltCl+Olc,QM'A.,EX'I+
In the event that some results are not available the report shall be submitted noting and explaining the reasons for the missinq results.The missing data shall be submitted as soon as possible in a supplementary report.
OCO~ttIdH~PPPAILEL,CXBRKPvL<<H~Kvu.S.(~~3~v)rLPITS~~IL3IPRa<>~W~IISCRICEH2CAHWHPdlDTIM&+PCS'~HIS+
S US QU EHA N NA S ES-ER-OL The reports shall include either explicitly or by reference to other documentation, the following:
NalH'k@HIQKLS tALLIS)PQg)~~H4H~CvHBThe%)PAC.TCILIW IPRIczcF~&cb~CCrIPhaCP~~I55bJICvI~H'g-I"~~ACTCC.i~IIIdHpIIIITACV I-EIpL5(,5;s,~3C%EL~'PCcCCC,5HulH~~+ICALr~luEAVCAr~lmmII43HcrHalLcm~~immikeAN~ImIHl5iiL~
a summary description of the radiological environmental monitorinq program including sampling methods for each sample type, size and physical characteristics of each sample type, sample preparation methods analytical methods, and measurinq equipment used;a map of all sampling locations..the results of the land use censuses and the results of the Applicant's participation in the Environmental Protection Agency's Environmental Radioactivity Laboratory Intercomparisons Studies (Crosscheck)
tCQ$5NATICNIIINcvsnu~cBmocIIIiIHCCRC.NISI~TOTAL~WAWHO@%.SALESIMDV5TTRIAL ScCTAExhibitV SUSQUEHANNASES-ER-OL contaminated byairborneradioiodine isapotential sourceofexposure.
Proqram.B.Non-routine Radiological Fnvironmental Operatinq Reports If a confirmed measured radionuclide concentration in an environmental sampling medium averaged over any quarter samplinq period exceeds the reporting level given in Table F-4, Reportinq Levels.for Non-Routine Operation, a written report shall be submitted to the Director of the NBC Regional Office (with a copy to the Director, Office of Nuclear Reactor Regulation) within 30 days from the end of the quarter.A confirmatory reanalysis of the original, a duplicate or a new sample may be desirable, as appropriate.
Samplesfrommilkanimalsareconsidered abetterindicator ofradioiodine intheenvironment thanvegetation.
The results of the confirmatory analysis shall be completed at the earliest time consistent with the analysis, but in any case within 30 days except in the case of the strontium analysis.Zf it can be demonstrated that the level is not a result of station effluents (i.e., by comparison with control station or preoperational data)a report need not be submitted, but shall be discussed in the annual report.If radionuclides other than those in Table-F-4 are detected and are due from station effluents, a reporting level is exceeded if the potential annual dose to an individual is equal to or greater than the design objective doses of 10 CFR Part 50, Appendix I This report shall include an evaluation of a release conditions, environmental factors or other aspects necessary to explain the anomalous result SUSQUEHANNA SFS-ER OL TABLE F-2 SUSQUEHANNA SES OPERATIONAL RADIOLOGICAL ENVIRONMENTAL HONITORING PROGRAH Sam~le T pe Air Particulates SS-AP-551 SS-AP-1152 SS-AP-9A1 SS-AP-12E1 SS-AP-7Hl Air Iodine SS-AI-551 SS-AI-1152 SS-AI-9A1 SS-AI-12El SS-AI-7H1 Surface Water SS-SW-5S2 SS-SW-12F1 Dr~inkin Water SS-PWT-12F2 SS-PWT-12H2 Fish**SS-AQF-6AI SS-AQF-2G1 Sediment SS-AQS-llcl Milk SS-H-5B1 SS-M-12B1 SS-H-1282 SS-H-7H2 Location++North of I.A.SW corner of si te Near Transmission Field Berwi ck Hospital PPEtL Roof North of I.A.SW corner of site Near Transmission Field Berwick Hospital PPSL Roof At I.A.Berwick Bridge Berwick Water Co.(treated)Danvi lie Water Co.(treated)Outfall Upstream Hess Is, area Farm Schultz Farm Young Farm Crytal Springs Dairy Collection F~PB UMC*SA SA 2/H~Anal sis Gross Beta Galena Emitters I-131 Gama Emitters H-3 Gross Beta Gamma Emi tters H-3 Gama Emi tters Gamma Emi tters I-131 Gama Emitters Analyti cal F~re Cene*W QC H QC SA SA 2/H 2/H Uni ts pCi/m3 pCi/m pCi/m pCi/1 pCi/1 pCi/1 pCi/1 pCi/1 pCi/g(wet)
Ifthecensusrevealsmilkanimalsarenotpresentorareunavailable forsampling, thenveqetation maybesampled.The500-sq.ft.garden,considering 20%usedforgrowinggreenleafyvegetables andavegetation yieldof2kg/m>willproducethe26kq/yrassumedin~Reula~torGuide1.109(March1974)forchildconsumption ofleafyveqetation.
PCi/9(dry) pCi/1 pCi/1 SUSQUEHANNA SES-ER-OL TABLE F-2 (cont.)SUSQUEHANNA SES OPERATIONAL RADIOLOGICAL ENVIRONMENTAL HONITORING PROGRAH~Sam le T e Food Products SS-FP-5B1 Direct Radiation SS-ID-3S2 SS-I D-4S1 SS-ID-551 SS-ID-7S1 SS-ID-11S2 SS-I D-9AI SS-ID-12E1 SS-ID-7HI Location++Farm Susquehanna River Susquehanna River North of I.A.On 230 KV Tower On 230 KV Tower Near Transmission Field Berwick Hospital PP&L Roof Collection
Theoptiontoconsiderthegardentobeatthenearestresidence isconservative andthoselocations maybeusedtocalculate dosesduetoradioactive effluentreleasesinplaceoftheactuallocations whichwouldbedetermined bythecensus.Thepermission ofdeviations fromthesamplingscheduleisbasedontherecognition ofunavoidable practical difficulties whichintheabsenceofthepermitted deviations wouldresultinviolation ofthespecifications.
~Fee mene*~Anal sis Ganma Emitters Gama Dose Analytical
Therequirement fortheparticipation intheEPAcross-check program,orsimilarprogram,isbasedontheneedforindependent checksontheprecision andaccuracyofthemeasurements ofradioactive materialinenvironmental monitorinq inordertodemonstrate thevalidityoftheresults.~ReoetingRequirement A.AnnualEnvironmental Operatinq Report,PartB,Radiological.
~Fre mene*Uni ts pCi/g(wet) mrem/std.mo Frequency Codes: W=Weekly;H=Monthly;Q=Quarterly; SA=Semi-Annual; A=Annual;2/H=twice each month;C Composite.
Areportontheradiological environmental surveillance proqramforthepreviouscalenderyearshallbesubmitted totheDirectoroftheNRCRegionalOffice(withacopytotheDirector, OfficeofNuclearReactorRequlation) asaseparatedocumentinMayofeachyear.Theperiodofthefirstreportshallbeginwiththedateofinitialcriticality Thereportshallincludea.summary(formatofTableF-1,Environmental Monitoring ProgramSummary)interpretations, andstatistical evaluation oftheresultsoftheradiological environmental surveillance activities forthereportperiod,includinq acomparison withoperational,
Important classes of fish will be analyzed separately.(bottom feeders and game fish)Hilk collected and analyzed semi-monthly from April through October-monthly during other months.Shown in Figure.
: controls, preoperational studies(asappropriate) andpreviousenvironmental surveillance reportsandanassessment oftheobservedimpactsofthestationoperation ontheenvironment.
SUSQUEHANNA SES ER OL TABLE F-3 DETECTION CAPABILITIES FOR ENVIRONMENTAL SAMPLE ANALYSIS MINIMUM DETECTABLE LEVEL (MDL)Analys is Water (pCi/l)Airborne Particulate or Gas (pCi/m')Fish (pCi/kg-wet)
Intheeventthatsomeresultsarenotavailable thereportshallbesubmitted notingandexplaining thereasonsforthemissinqresults.Themissingdatashallbesubmitted assoonaspossibleinasupplementary report.
Mi 1 k Food Products Sediment (pCi/1)(pCi/kg-wet)(pCi/kg-dry)
SUSQUEHANNASES-ER-OLThereportsshallincludeeitherexplicitly orbyreference tootherdocumentation, thefollowing:
Gross Beta H-3 Mn-54 Fe-59 Co-58,60 Zn-65 ZrNb-95 I-131 Cs-134,137 BaLa-140 200 10 20 10 20 0.3 10 10 7 x 10 5x10 5 x 10 85 170 85 170 85 5c 10 10 16c,d 50 100 SUSQUEHANNA SES-ER-OL Table F-3 (Cont'd)~Acceptable detection capabilities for thermoluminescent dosimeters used for environmental measurements are given in Regulatory Guide 4.13, July 1977.Indicates acceptable detection capabilities for radioactive materials in environmental samples.These detection capabilities are tabulated in terms of the minimum detectable level (MDLs).The NOL is defined, for purposes of this Table, as that concentration of radioactive material in a sample that will yield a net count which is different from the background count by three times the standard deviation after background count.For a particular measurement system (which may include radiochemical separation):
asummarydescription oftheradiological environmental monitorinq programincluding samplingmethodsforeachsampletype,sizeandphysicalcharacteristics ofeachsampletype,samplepreparation methodsanalytical methods,andmeasurinq equipment used;amapofallsamplinglocations.
MDL=3 00 Sb E x V x 2.22 x Y x exp(-X t)where, NOL is minimum detectable level as defined above (as pCi per unit mass or volume)Sb is the standard deviation of the background counting rate or of the counting rate of a blank sample as appropriate (as counts per minute)E is the counting efficiency (as counts per disintegration)
.theresultsofthelandusecensusesandtheresultsoftheApplicant's participation intheEnvironmental Protection Agency'sEnvironmental Radioactivity Laboratory Intercomparisons Studies(Crosscheck)
V is the sample size (in units of mass of volume)2e22 is the number of disintegrations per minute per picocurie Y is the fractional radiochemical yield (when applicable) is the radioactive decay constant for the particular radionuclide is the elapsed time between sample collection and counting The value of S used in the calculation of the NOL for a particular measurement system should e based on the actual observed variance of the background counting rate or of the counting rate of the blank samples (as appropriate) rather than on an unverified theoretically predicated variance.In calculating the MDL for a radionuclide determined by gama-ray spectrometry, the background should include the typical contributions of other radionuclides normally present in the sample (e.q., potassium-40 in milk samples).Typical values of E,V,Y, and t should be used in the calculation.
Proqram.B.Non-routine Radiological Fnvironmental Operatinq ReportsIfaconfirmed measuredradionuclide concentration inanenvironmental samplingmediumaveragedoveranyquartersamplinqperiodexceedsthereporting levelgiveninTableF-4,Reportinq Levels.forNon-Routine Operation, awrittenreportshallbesubmitted totheDirectoroftheNBCRegionalOffice(withacopytotheDirector, OfficeofNuclearReactorRegulation) within30daysfromtheendofthequarter.Aconfirmatory reanalysis oftheoriginal, aduplicate oranewsamplemaybedesirable, asappropriate.
It should be recognized that the NOL is defined as~a riori (before the fact)limit representing the capability of a measurement system and not as f t f ill i f p SUSQUEHANNA SES-ER-OL Table F-3 (Cont'd)c.MDLs for I-131 in water, milk and other food products correspond to one-quarter of the Appendix I (10 CFR Part 50)design objective dose-equivalent of 15 mrem/year using the assumptions given in Regulatory Guide 1.109 except for an infant consuming 330 1/yr of drink water.d.MDL for leafy vegetables.}}
Theresultsoftheconfirmatory analysisshallbecompleted attheearliesttimeconsistent withtheanalysis, butinanycasewithin30daysexceptinthecaseofthestrontium analysis.
Zfitcanbedemonstrated thatthelevelisnotaresultofstationeffluents (i.e.,bycomparison withcontrolstationorpreoperational data)areportneednotbesubmitted, butshallbediscussed intheannualreport.Ifradionuclides otherthanthoseinTable-F-4aredetectedandareduefromstationeffluents, areporting levelisexceededifthepotential annualdosetoanindividual isequaltoorgreaterthanthedesignobjective dosesof10CFRPart50,AppendixIThisreportshallincludeanevaluation ofareleaseconditions, environmental factorsorotheraspectsnecessary toexplaintheanomalous result SUSQUEHANNA SFS-EROLTABLEF-2SUSQUEHANNA SESOPERATIONAL RADIOLOGICAL ENVIRONMENTAL HONITORING PROGRAHSam~leTpeAirParticulates SS-AP-551 SS-AP-1152 SS-AP-9A1 SS-AP-12E1 SS-AP-7Hl AirIodineSS-AI-551 SS-AI-1152 SS-AI-9A1 SS-AI-12El SS-AI-7H1 SurfaceWaterSS-SW-5S2 SS-SW-12F1 Dr~inkinWaterSS-PWT-12F2SS-PWT-12H2 Fish**SS-AQF-6AI SS-AQF-2G1 SedimentSS-AQS-llcl MilkSS-H-5B1SS-M-12B1 SS-H-1282 SS-H-7H2Location++NorthofI.A.SWcornerofsiteNearTransmission FieldBerwickHospitalPPEtLRoofNorthofI.A.SWcornerofsiteNearTransmission FieldBerwickHospitalPPSLRoofAtI.A.BerwickBridgeBerwickWaterCo.(treated)
DanvilieWaterCo.(treated)
OutfallUpstreamHessIs,areaFarmSchultzFarmYoungFarmCrytalSpringsDairyCollection F~PBUMC*SASA2/H~AnalsisGrossBetaGalenaEmittersI-131GamaEmittersH-3GrossBetaGammaEmittersH-3GamaEmittersGammaEmittersI-131GamaEmittersAnalyticalF~reCene*WQCHQCSASA2/H2/HUnitspCi/m3pCi/mpCi/mpCi/1pCi/1pCi/1pCi/1pCi/1pCi/g(wet)
PCi/9(dry) pCi/1pCi/1 SUSQUEHANNA SES-ER-OL TABLEF-2(cont.)SUSQUEHANNA SESOPERATIONAL RADIOLOGICAL ENVIRONMENTAL HONITORING PROGRAH~SamleTeFoodProductsSS-FP-5B1 DirectRadiation SS-ID-3S2 SS-ID-4S1SS-ID-551SS-ID-7S1 SS-ID-11S2 SS-ID-9AISS-ID-12E1SS-ID-7HILocation++FarmSusquehanna RiverSusquehanna RiverNorthofI.A.On230KVTowerOn230KVTowerNearTransmission FieldBerwickHospitalPP&LRoofCollection
~Feemene*~AnalsisGanmaEmittersGamaDoseAnalytical
~Fremene*UnitspCi/g(wet) mrem/std.mo Frequency Codes:W=Weekly;H=Monthly;Q=Quarterly; SA=Semi-Annual; A=Annual;2/H=twiceeachmonth;CComposite.
Important classesoffishwillbeanalyzedseparately.
(bottomfeedersandgamefish)Hilkcollected andanalyzedsemi-monthly fromAprilthroughOctober-monthlyduringothermonths.ShowninFigure.
SUSQUEHANNA SESEROLTABLEF-3DETECTION CAPABILITIES FORENVIRONMENTAL SAMPLEANALYSISMINIMUMDETECTABLE LEVEL(MDL)AnalysisWater(pCi/l)AirborneParticulate orGas(pCi/m')Fish(pCi/kg-wet)
Mi1kFoodProductsSediment(pCi/1)(pCi/kg-wet)
(pCi/kg-dry)
GrossBetaH-3Mn-54Fe-59Co-58,60Zn-65ZrNb-95I-131Cs-134,137 BaLa-140200102010200.310107x105x105x108517085170855c101016c,d50100 SUSQUEHANNA SES-ER-OL TableF-3(Cont'd)~Acceptable detection capabilities forthermoluminescent dosimeters usedforenvironmental measurements aregiveninRegulatory Guide4.13,July1977.Indicates acceptable detection capabilities forradioactive materials inenvironmental samples.Thesedetection capabilities aretabulated intermsoftheminimumdetectable level(MDLs).TheNOLisdefined,forpurposesofthisTable,asthatconcentration ofradioactive materialinasamplethatwillyieldanetcountwhichisdifferent fromthebackground countbythreetimesthestandarddeviation afterbackground count.Foraparticular measurement system(whichmayincluderadiochemical separation):
MDL=300SbExVx2.22xYxexp(-Xt)where,NOLisminimumdetectable levelasdefinedabove(aspCiperunitmassorvolume)Sbisthestandarddeviation ofthebackground countingrateorofthecountingrateofablanksampleasappropriate (ascountsperminute)Eisthecountingefficiency (ascountsperdisintegration)
Visthesamplesize(inunitsofmassofvolume)2e22isthenumberofdisintegrations perminuteperpicocurie Yisthefractional radiochemical yield(whenapplicable) istheradioactive decayconstantfortheparticular radionuclide istheelapsedtimebetweensamplecollection andcountingThevalueofSusedinthecalculation oftheNOLforaparticular measurement systemshouldebasedontheactualobservedvarianceofthebackground countingrateorofthecountingrateoftheblanksamples(asappropriate) ratherthanonanunverified theoretically predicated variance.
Incalculating theMDLforaradionuclide determined bygama-rayspectrometry, thebackground shouldincludethetypicalcontributions ofotherradionuclides normallypresentinthesample(e.q.,potassium-40 inmilksamples).
TypicalvaluesofE,V,Y,andtshouldbeusedinthecalculation.
Itshouldberecognized thattheNOLisdefinedas~ariori(beforethefact)limitrepresenting thecapability ofameasurement systemandnotasftfillifp SUSQUEHANNA SES-ER-OL TableF-3(Cont'd)c.MDLsforI-131inwater,milkandotherfoodproductscorrespond toone-quarter oftheAppendixI(10CFRPart50)designobjective dose-equivalent of15mrem/yearusingtheassumptions giveninRegulatory Guide1.109exceptforaninfantconsuming 3301/yrofdrinkwater.d.MDLforleafyvegetables.}}

Revision as of 05:12, 6 July 2018

Susquehanna Units 1 and 2 - Amendment No. 4 Rev. 1 to Environmental Report
ML18023B081
Person / Time
Site: Susquehanna  Talen Energy icon.png
Issue date: 03/05/1979
From:
Pennsylvania Power & Light Co
To:
Office of Nuclear Reactor Regulation
References
Download: ML18023B081 (58)


Text

SUSQUEHANNA SES-ER-OL SECTION TITLE VOLUME APP EN DX'XZS....~.............

~XII B1 AN EVALUA ON OF THE COST OF SF.VICE IMPACT OF A DELAY N THE IN-SERVICE D TES OF SUSQUEHANNA ES (JANUARY 1978............IXI CURRENT LONG-RA GE FORECAS ENERGY SALES 6 PEAK LOAD 1976-1 0....................

~~IXI APPLICANT'S FORECAS NG METHODOLOGY KMH SALES AND PEAK LOADS CE!1BER, 1976.........IXI NATXONMIDE FUEL EilZ GENCY ZSPONSZ TO FPC ORDER NO 496..............

~XII SUSQUEHANNA RIVE MATER ANALYSZ

SUMMARY

..III EQUATIONS AND SSUMPTIONS UTILIZED N THE CALCULATION 0 INDIVIDUAL AND POPULA ON DOSES TO MAN.'IX ENVIRON%EN AL TECHNXCA L S PECIFXC ATION S..XII SUSQUEHANNA SES-ER-OL TABLE 1.1-3 1977 PROJECTION OF APPLICAN'A LOADS-CAPACITY-RESERVES (HIGH LOAD PROJECTION Year Winter Peak MWe 1978 4960 1979 5320 1980 5670 1981 6100 1982 6480 1983 6840 1984 7200 1985 7570 Capacity Changes Fossil (Oil)Nuclear Hydro Reratings 945(')945(l)63(2)Total Capacities Fossil (Coal)Fossil (Oil)CT 6 (j~sel Hydro Nuclear Firm Purchase Capacity Transactions 4145 1640 539 146 76 (41)4145 1640 539 146 76 (50)4145 1640 539 146 76 4145 1640 539 146 1890 76 4145 4145 4145 4145 1640 1640 1640 1640 539 539 539 539 146 146 146 209 945 1890 1890 1890 76 76 76 76 Total MWe 6505 6496 6436 7426 8405 8374 8343 8374 Reserve over winter peak: With Susquehanna MWe Capacity X of Load 1326 22 1925 30 1534 1143 22 16 804 ll Without Susquehanna MWe Capacity%of Load 1545 31 1176 22 766 14 326 5 (65)(436)(807)(1126)(1)(6)(ll)(15)With Susquehanna But Without Oil S Hydro Generation Without Susquehanna~

Oil 8 Hydro Generation Hwe Capacity (856)(1225)(17)(23)(1075)(476)(867)(1258)(1660)(18)(7)(13)(17)(22)(1635)(2075)(2466)(2837)(3208)(3590)(29)(34)(38)(41)(45)(47)Note: See Footnotes Following Table 1.1-6.

SUSQUEHANNA SES"ER-OL TABLE 1.1-4 1977 PROJECTION OF APPLICAFA LOADS-CAPACITY-RESERVES MID-RANGE LOAD PROJECTION)

Year Winter Peak MWe Capacity Changes Fossil (Oil)Nuclear Hydro Reratings 1978 4820 1979 5050 1980 5310 1981 5690 945(l)1982 5990 945"'983 6280 1984 6560 1985 6850 63(2)Total Capacities Fossil (Coal)Fossil (Oil)CT 6 (j~sel Hydro Nuclear Firm Purchase Capacity Transactions Total MWe 4145 1640 539 146 76 (41)6505 4145 1640 539 146 76 (50)6496 4145 1640 539 146 76~(110 6436 4145 1640 539 146 945 76 (65)7426 4145 1640 539 146 1890 76 (31)8405 4145 1640 539 146 1890 76 (62)8374 4145 1640 539 146 1890 76 4145 1640 539 209 1890 76~(93 (125)8343 8374 Reserve over winter peak: With Susquehanna MWe Capacity g of Load 1736 2415 31 40 2094 33 1783 1524'27 22 Without Susquehanna MWe Capacity$of Load 1685 1446 35 29 1126 21 736 13 425 7 124 2 (167)(406)(3)(6)With Susquehanna But Without Oil 6 Hydro Generation (665)(12)14 (307)(618)(940)1 (5)(9)(14)Without Susquehanna~

Oil 6 Hydro Generation (716)(955)(1275)(1665)(1976)Mwe Capacity (15)(19)(24)(29)(33)NOTE: See Footnotes Following Table 1.1-6 (2277)(2568)(2870)(36), (39)(42)

SUS(UEHANNA SES-ER-OL TABLE 1.1-5 1977 PROJECTION OF APPLICANT LOADS-CAPACITY"RESERVES (IOW IOAD PROJECTION Year Winter Peak MWe Capacity Changes Fossil (Oil)Nuclear Hydro Reratings 1978 4650 1979 4720 1980 4910 1981 5170 945"'982 5390 945(" 1983 5650 1984 5920 1985 6050 63(2)Total Capacities Fossil (Coal)Fossil (Oil)CT 8 (j~sel Hydro Nuclear Firm Purchase Capacity Transactions Total Mwe 4145 1640 539 146 76 4145 1640 539 146 76 4145 1640 539 146 76 4145 1640 539 146 945 76 4145 4145 4145 1640 1640 1640 539 539 539 146 146 146 1890 1890 1890 76 76 76 6505 6496 6436 7426 8405 8374 8343 4145 1640 539 146 1890 76 (125)8374 Reserve over winter peak: With Susquehanna MWe Capacity~of Load 2256 3015 44 56 2724 48 2423 2324 41 38 Without Susquehanna MWe Capacity 4 of Load With Susquehanna But Without Oil 6 Hydro Generation MWe Capacity g of Load 1855 1776 1526 40 38 31 (145)(3)614 11 1256 1025 24 19 754 13 323 6 473 8 22 1 394 7 (140)(2)Without Susquehanna>

Oil 8 Hydro Generation (546)(625)MWe Capacity (12)(13)g of Load NOTE: See Footnotes Following Table 1.1-6.(875)(1 145)(1376)(1647)(18)(22)(26)(29)(1928)(2070)(33)i (34)

SUSQUEHANNA SES-ER-OL TABLE 1.1-6 1977 PROJECTION OF APPLICAN'8 LOADS-CAPACITY-RESERVES (LOW-LOW LOAD PROJECTION)

Year Winter Peak HWe Capacity Changes Fossil (Oil)Nuclear Hydro Reratings 1978 4530 1979 4580 1980 4720 1981 4890 945(l)1982 5050 945()1983 5230 1984 5420 1985 5500 63(2)Total Capacities Fossil (Coal)Fossil (Oil)CT 8 (j~sel Hydro Nuclear Fixm Purchase Capacity Transactions Total HWe 4145 1640 539 146 76 (41)6505 4145 1640 539 146 76 (50)6496 4145 1640 539 146 76~llO 6436 (65)7426 (31)8405 (62)8374 (93)8343 (125)8374 4145 4145 4145 4145 4145 1640 1640 1640 1640 1640 539 539 539 539 539 146 146 146 146 209 945 1890 1890 1890 1890 76 76 76 76 76 Reserve over winter peak: With Susquehanna NWe Capacity$of Load 2536 52 3355 3144 2923 66 60 54 2874 52 Without Susquehanna MWe Capacity g of Load 1975 44 1916 42 1716 1536 36 31 1365 27 1174 22 973 18 944 17 With Susquehanna But Without Oil 6 Hydro Generation MWe Capacity g of Load Without Susquehanna, Oil 6 Hydro Generation (426)MWe Capacity (9)g of Load 135 3 (485)(685)(865)(11)(15)(18)954 19 743 14 (1036)(1227)(21)(23)522 10 410 7 (1428)(1520)(26)(28)NOTE: See Footnotes Following Table 1.1-6 S USQ UEH A N NA S ES-E R-OL 2 3.1 2.2 Tornadoes The incidence of tornadoes in the site area is very low.Between the years 1950 and 1973 only 38 tornadoes were reported within 50 miles of the site.Tornado activity is at a maximum during the summer months with most tornadoes occurring in the late afternoon or evening.Figure 2.3-1, Tornado Occurrence

<<nd Intensity in the Susquehanna SZS Reqion, is a histogram for the years 1953-1962 showing tornado frequency by month, hour and intensity within a 3 by 3~square which is centered on the site.The intensity cateqories are based on the Fujita tornado intensity classification (Ref.2.3-5).Prom Figure 2.3-1 it can be seen that maximum tornado occurrence is in the summer.Diurnally, tornado frequency reaches a maximum during late afternoon, shortly after the period of greatest instability 2 3.1.2 3 Th>>ndec storms Thunderstorms in the area are usually of brief duration and concentrated in the warm months.They are responsible foc most of the summertime rainfall which normally avecaqes around 3.7 inches per month at Avoca.Based on a 19 year average at Avoca the mean number of"days with thunder heard" is 30 (Ref 2.3-3).A monthly breakdown of the mean number of thunderstorm days that is representative of the site is shown in Table 2.3-2, Th understocm Days for Avoca.2.3.1 2.4 L~iht ning There is neither documentation nor direct measurement of the occurrence of lightning other than the observation of associated thunder.Local climatological data tabulated by the National Weather Service (Ref.2.3-3)does not provide information reqardinq the incidence, severity.or frequency of lightning occurrences A.thunderstocm can usually be heard unless the liqhtning causing the thunder is more than 15 miles away;therefore, thunder incidence can presumably be used to confirm the presence of some lightning The number of lightning strikes per square mile per year has been established by, Uman (Ref.2.3-6).The combined results of several studies summarized ny Uman indicate that the number of flashes to the qround pec square mile per year is between 0 05 and 0.80 times the number of thunderstorm days pec year.The mean number of days with thunderstorms probably over estimates the actual occurrence of cloud-to-ground lightning since some thunderstocms probably contain only cloud-to-cloud lightning.

2~3 3 SUSQUEHANNA S ES-ER-OL Therefore.

if the annual thunderstorm frequency at Avoca is used (30 days), the number of: ground lightning strikes is between two and 24.2 3 1 2 5 Hail Hail in the site region sometimes falls from severe thunderstorms.

Because hail f alls in narrow swa ths, only a small fraction of occurrences is recorded at regular reporting stations The average annual number of days with hail at a point in the area is 23.The occurrence of large hail (greater than 0.75 inches diameter)averaqes one or two occurrences annually Accordinq to Pautz (Ref.2.3-7)the number of hailstorms with hail 0.75 inch or greater in a one-degree longitude-latitude square area in the vicinity of the site for the period 1955-1967 was about five For Avoca from 1973-75 there was one hailstorm in June and one in July of 1973 and 1974.Xn 1975 there was also one hailstorm in August and one in October There were no occurrences of hail recorded in 1976 at Avoca (Ref.2.3-3)2 3.1 2 6 Extreme Minds Strong winds occur in Pennsylvania as a result of occasional hurricanes, thunderstorms, tornadoes and tropical storms.The followinq is the fastest mile of wind and its associated direction, by month, at Avoca (1955-1976)(Ref.2.3-3).Fastest Mile of Wind Month mph Direction Month mph Direction January February March April May June 43 60 49 47 40 43 SE W S NW NW W July 42 NW Auqust 50 NE September 38 SM October 38 E November 45 S December 47 SM The 50-year and 100-year mean fastest mile wind speeds for the site area are 75 miles per hour and 80 miles per hour, respectively (Ref.2.3-8).Accordinq to Pautz, there were eight windstorms 50 knots and qreater for the one degree latitude-longitude square that includes the Susquehanna SES for the period 1955-1967 (Ref.2 3-7).2 3-4 SUSQUEHANNA SES-ER-G'i.

TABLE 2.3-33 LONG-TERM TEMPERATURE (F)AT AVOCA (Period of Record: 1956-1974)

Month January February March April June July August September October November December 33.5 18.4 35.3 44.7 58.9 70.0 19.3 27.2 38.0 47.8 79.0 83.0 56.8 61.3 80.7 59.2 73.6 52.1 63.0 48.8 36.1 42.2 32.8 22.0~Dail Max~Dail Mia Mean 26.0 27.3 36.0 48.5 58.9 67.9 72.2 70.0 62.9 52.6 40.8 29.1 67-10 62 78 89 15 93 27 97 34 101 45 94 43 95 30 84 19 77 10 65 Extreme Hicihest lowest Annual 58.9 39.8 49.4 101 Ref.2.3-3 SUSQUEHANNA SES-ER-OL TABLE 2.3-49 PRECIPITATION DATA FOR AVOCA (Period of Record: 1956-1974)

Month January February March April May Total (in inches)2.04 1.96 2.50 3.06 3.50 Greatest 24-Hour (in inches)1.52 1.60 2.20 1.59 2.58 June July August September October November December 3.40 4.09 3.21 2.82 2.71 3.01 2.51 3.61 2.33 3.18 3.09 2.61 2.91 2.30 Annual 34.81 3.61 Ref.2.3-3 SUSQUEHANNA SES-ER-OL.

TABLE 2.3-81 JOINT FRE UENCY (%)OF WIND DIRECTION, WIND SPEED AND STABILITY FOR AVOCA (Period of Record: 1971-1975)

Stability Class B Wind Speed (kts)Se'ctor NNE NE ENE ESE SE SSE SSW SW WSW NW NNW Total 0-3 898 975 654 4-6.1507.0548.0548 7-10.1164.0548.0616 424 1675 898 991 1773.0137.0890.1507.2055.2877.0137.0205.0959.1507.2123 2118.2493.1301 1449.1918 1449.1986 748.1096 6507 1.9726.1164.0890.1027 1.2192 1112.0411.0137 768.0274.0342 516.0205 0 528.0274.0068 11-16 17-21>21 Total.3569.2071.1819.1660.1385.0721.0870.0698.2771.3364.4553~6773.6913.4531.3856.2871 Relative frequency of occurrences of B Stability=4.8425 Ref.2.3-4 SUSQUEHANNA SES-ER-OL SECTION TITLE VOLUME APPENDICIESo o r o o o o o o e o~o o o o o o o o o r o or o o o o o o o o o o o III B1 AN EVALUATION OF THE COST OF SERVICE.IMPACT OF A DELAY IN THE IN-SERVICE DATES OF SUSQUEHANNA SES (JANUARY 1978).......III CURRENT LONG-RANGE FORECAST ENERGY SALES 6 PEAK LOAD 1976-1990.................

III B2 APPLICANT' FORECASTING METHODOLOGY KWH SALES AND PEAK LOADS DECEMBER, 1976..III NATIONWIDE FUEL EMERGENCY RESPONSE TO FPC ORDER NO 496.............

~III SUSQUEHANNA RIVER WATER ANALYSES

SUMMARY

...III EQUATIONS AND ASSUMPTIONS UTXLIZ ED IN THE CALCULATION OF IN DIVIDUAL AND POPULATION DOSESTOMANoorooooo

~or eooeoooooooooor

~ooo coro~III ENVIRONMENTAL TECH NICA L S PECIFIC ATIONS...~III P i t~P E'I SUSQU EHANNA S ES-ER-OL site)and at Danville (about 31 miles (49.9 km)downstream.

The Corps of Engineers has compiled flood stage and discharge.information for the Susquehanna River at Wilkes-Barre (Ref.2.4-7).These data are based on records of flood stages dating from 1991 Data for the four most severe floods of record are presented in Table 2.4-5, Historic Floods in the Vicinity of the Susquehanna SES Table 2.4-5 also includes the stages and discharges f or floods at the site and at Danville.The flood frequency characteristics of the Susquehanna as measured at Danville are illustrated in Figure 2.4-6, Flood Discharge Frequency.

The passaqe of Tropical Storm Agnes through.Pennsylvania on June 22 and 23, 1972 resulted in record flood levels in the Susquehanna River Basin Flood crests exceeded the previous record flood level.of 1936 at Wilkes-Barre by 7 5 feet (2.3 m).At Danville, a local maximum qaqe level resulting from a 1904 ice jam was exceeded by 1.6 feet (0.5 m).Peak discharqe at Wilkes-Barre was an estimated 345,000 cfs (9,770 m~/sec)or a unit discharge of 34.5 cubic feet per second per sguare mile (cfsm)(0 4 m~/sec/km~)

.Accumulated runoff for the drainage area above Wilkes-Barre for the period of 0000 hours0 days <br />0 hours <br />0 weeks <br />0 months <br />, June 21, 1972 through 2200 hours0.0255 days <br />0.611 hours <br />0.00364 weeks <br />8.371e-4 months <br />, June 27, 1972 totaled 4.32 inches (11.0 cm)(Ref.2 4-13).2 4.2 5 Low Plows Long term records from the USGS gaging stations at Danville and Wilkes-Barre provide the data base for the low flew f requency analyses presented in this Subsection.

Long duration low flow f requency analysis has been performed by the Pennsylvania Department of Environmental Resources (DER).The resulting curves for low f3.ow durations of two to 60 months and recurrence intervals up to 100 years for Danville and Wilkes-Barre are provided in Figures 2.4-7, Low Flow Duration at Danville and 2.4-8~Low Flow Duration at Wilkes-Barre, respectively.

Tables 2.4-6 and 2.4-7, Maqnitude and Frequency of Annual Low Flow of the Susquehanna River at Danville and Wilkes-Barre, Pa.respectively, discuss the discharge for different recurrence intervals.

Tables 2.4-8 and 2.4-9, Duration Table of Daily Flow of the Susquehanna River at Danville and Wilkes-Barre, Pa.respectively indicate the river discharge (Ref.2.4-14).The most extended drought period occurred in the 1960's.The lowest consecutive day flows for periods of 183 days and less have also occurred in this period The mean monthly flows at Danville and Wilkes-Barre are provided in Table 2.4-10a, Mean Monthly Drought Year Flow Sequences.

Mean Daily Flows During 1964 Drought, Table 2.4-10b for these two stations are provided for the four lowest flow months of this year 2 4-5 S USQ U EH A NNA S ES-E R-OL A policy decision'of the Susquehanna River Basin Commission reqardinq consumptive withdrawals during low flow periods provides that natural flows during droughts will not he diminished by future water users.On September 30 1976, this policy decision was implemented as an Amendment to 18 CFR Part 80'3 (Susquehanna River Basin Commission, Subpart D-Standards for Review, Section 803.61, Consumptive Uses of Mater)(Ref.2.4-15).Compensation shall be reguired for consumptive uses of water during periods of low flow.The provisions of this regulation apply to consumptive uses initiated since January 23, 1971 2 4 2 6 Sedimentation Annual sediment yields in the reqion surrounding the site are spacially uniform.Neasurements at Towanda, Pa.about 105 miles (169 km)above the station, indicate on annua'ediment yield of 150 tons/sq mi (52.5 metric tons/km~)from a drainaqe area of 7797 sq mi (20,194 km~).Annual yields at Danville, 11,220 sq mi (29,060 km~)drainage area are estimated to be 140 tons/sq mi (49.0 metric tons/km~)(Ref 2 4-8).Daily sediment discharges at individual stations are highly variable The daily sediment discharqe at Danville ranqes from a high of 556, 000 tons/day (504,400 metric tons/day)to a low of 18 tons/day (16.3 metric tons/day).Mater quality samplinq at the site included measurement of total suspended solids A range of values from 1.6 mg/1 to 912.6 mq/1 with an averaqe value of 57.0 mg/1 was found.These results are further reported in Subsection 2.4 3.Grain size analysis was performed on water samples taken in 1974 usinq an automatic image analyzer.The grain size determination was performed on treated and untreated river water samples.The results for the untreated samples are reported in Table 2 4-11, Sediment Grain Size Distribution.

2 4 2 7 Mater Impoundments The Susquehanna River supplies all the water required for normal station operation.

A seven-acre (2.8 ha.)spray'ond is located onsite to supply water to emergency heat dissipation systems.The warmed water from the reactors is cooled via the pond's spray system and then recirculated throuqh the emergency cooling systems.This spray pond has a relatively impervious liner.It is free-form in shape to conform to the natural topography of the area.Embankments and ditches are provided to direct surface water 2.4-6 SUS(}UEHANNA SES-ER-OL TABLE 2.4-2 MONTHLY AVERAGE RIVER CONDITIONS STAGE, VEIOCITY AND DISCHARGE OCTOBER STATION (River Mile)~Sunbury (122.0)STAGE VELOCITY DIS(HARGE (Ft.msl)(Ft/sec)(Ft/sec)Present Pro ected Present Pro ected Present Pro ected 420.9 420.9 2.0 1.9 9164 8631 Northumberland (123.5)Volverton Sta.(128.5)Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162.4)Mapwallopen (163.9)Plant Site (165;5)Shickshinny (169.5)422.9 427.8 434.6 447.9 453.5 457.4 476.4 477.6 483.0 483.3 484.7 487.9 422.8 427.6 434.4 447.7 453.3'57.2 476.3 477.4 482.9 483.1 484.5 487.7 0.8 3.0 1.8 1.6 1.0 1.6 1.9 1.6 1.5 1.0 2'0.7 3.3 1.8 1.6 1.0 1.5 1.0 1.9 1.5 1.4 0.9 2.7 5144 5122 5083 4939 4749 4749 4623 4623 4623 4623 4595 4570 4761 4742 4707 4590 4408 1 4408 4290 4290 4290 4290 4280 4270

SUS(}UEHANNA SES-ER-OL TABLE 2.4-2 (Continued)

STATION (River Mile)Sunbury (122.0)Northumberland (123.5)Wolverton Sta.(128.5)Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162.4)Wapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)425.0 429.8 437.1 451.2 456.2 460.0 478.9 479.8 484.8 485.5 487.4 490.8 424.9 429.7 437.0 451.1 456.1 59.9 478.8 479.7 484.8 485.4 487.3 490.7 1.0 2.4 2.2 1.9 1.5 2.2 1.6 2.0 2.1 2.4 1.6 3.9 1.0 2.4 2.2 1.9 1.5 2.1 1.5 2.0 2'2.3 1.6 3.9 12478 12095 12457 12077 12421 12045 12090 11741 11648 11307 11648 11307 11356 11023 11356 11023 11356 11023 11356 11023 11291 10976 11232 10932 STAGE VELOCITY DIS(HARGE (Ft.msl)(Ft/sec)(Ft/sec)Present Pro ected Present Pro ected Present Pro ected 422.0 421.9 3.4 3.4 21146 20613 SUSQUEHANNA SES-ER-OL TABLE 2.4-2 (Continued)

STATION (River Mile)STAGE VELOCITY DIS(HARGE (Ft.msl)(Ft/sec)(Pt/sec)Present Pro ected Present Pro ected Present Pro'ected Sunbury (122.0)Northumberland (123.5)Wolverton Sta.(128.5)Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162')Wapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)426.2 426.1 431.0 430.9 438.5 438.4 453.2 453.0 457.5 457.4 461.4 461.3 480.2 480.10 481.1 481.0 485'485.7-486.7 486.6 488.8 488.7 492.4 492.3 422.6 422.6 4.2 2.5 2.4 2.0 1.8 2.5 1.8 2.2 2.3 2.9 2.0 4.2 4.2 2.5 2.4 2.0 1.7 2.5 1.8 2.2 2.3 2.8 1.9 4.2 29842 18028 17958 17835 17348 16698 16698 16270 16270 16270 16270 16175 16089 29309 17645 17578 17459 16999 16357 16357 15937 15937 15937 15937 15860 15789

SUSQUEHANNA SES-ER-OL TABLE 2.4-2 (Continued)

STATION (River Mile)STAGE (Ft.msl)Present Pro'ected VELOCITY (Ft/sec)Present Pro ected DIS(HARGE (Ft/sec)Present Pro ected Sunbury (122.0)Northumberland (123.5)Volverton Sta.(128.5)Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162.4)Mapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)425.6 425.6 430.4 430.3 437.7 437.6 452.0 451.9 456.7 456.6 460.6 460.5 479.5 479.4 480.4 480.3 485.2 485.2 486.0 485.9 488.0 487.9 491.5 491.4 422.3 422.3 3.9 2.4 2.3 1.9 1.6 2.3-l.7 2.1 2.2 2.6 1.8 4.0 3.8 1.0 2.4 2.3 1.9 1.6 2.3 1.7 2.1 2.2 2.5 1.7 4.0 25852 14978 14908 14785 14349 13768 13768 13384 13384 13384 13384 13299 13222 25319 14595 14528 14409 14000 13427 13427 13051 13051 13051 13051 12984 12922

)0 SUSQUEHANNA SES-ER-OL TABLE 2.4-2 (Continued)

STATION (River Mile)STAGE (Ft.msl)Present Pro ected VELOCITY*(Ft/sec)Present Pro ected DIS(HARGE (Ft/sec)Present Pro ected Sunbury (122.0)Northumberland (123.5)Wolverton Sta.(128.5)Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162.4)Wapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)422.7 426.2 430.9 438.3 453.0 457.5 461.4 480.1 481.0 485.8 486.7 488.7 492.3 422.6 426.2 430.8 438.3 452.9 457.4 461.3 480.1 481.0 485.7 486.6 488.6 492.2 4.3 2.5 2.4 2.0 1.8 2.5 1.8 2.2 2.3 2.8 1.9 4.2 4.3 2.5 2.4 2.0 1.8 2.5 1.8 2.1 2.3 2.8 1.9 4.2 17576 17193 17479 17099 17308 16932 16920 16571 16685 16344 16685 16344 16071 15738 16071 15738 16071 15738 16071 15738 15828 15513 15759 15459 30704 30171 SUSQUEHANNA SES-ER-OL TABLE 2.4-2 (Continued)

STATION (River Mile)STAGE (Ft.msl)Present Pro ected VELOCITY (Ft/sec)Present Pro ected DIS)HARGE (Ft/sec)Present Pro ected Sunbury (122.0)Northumberland (123.5)Wolverton Sta.(128.5)Danville (134.7)428.7 428.7 433.4 433.4 441.2 441.1 424.4 424.4 5.6 1.3 2.7 2.8 5.6 1.3 2.7 2.8 55420 31852 31732 31521 54887 31469 31352 31143 Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (164.2)Wapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)456.7 460.4 464.4 482.9 483.8 488.0 489.4 491.9 495.9 456.7 460.3 464.4 482.8 483.7 488.0 489.4 491.8 495.9 2.4 2.3 3.1 2.5 2.6 2.9 3.8 2.7 5.0 2.4 2.3 3.1 2.5 2.6 2.9 3.8 2.7 5.0 31065 30458 30458 30058 30058 30058 30058 29969 29888 30716 30117 30117 29725 29725 29725 29725 29654 29588

SUSQUEHANNA SES-ER-OL TABLE 2.4-2 (Continued)

STATION (River Mile)STAGE (Ft.msl)Present Pro ected VELOCITY (Ft/sec)Present Pro ected DIS(HARGE (Ft/sec)Present Pro ected Sunbury (122.0)Northumberland (123.5)Wolverton'Sta.(128')Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162.4)Mapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)424.8 429.2 434.2 442.1 457.9 461.3 465.3 483.6 484.6 488.7 490.2 492.8 497.0 424.7 429.2 434.2 442.0 457.8 461;2 465.3 483.6 484.6 488.7 490.2 492.8 496.9 5.8 5.9 1.4 1.4 37415 37032 2.8 2.8 37256 36876 2.9 2.9 36978 36602 2.5 2.5 36331 35982 2.5 2.5 35469 35128 3.3 3-3 35469 35128 2.7 2.7 34900 34567 2.7 2.7 34900 34567 3.0 3.0 34900 34567 4.1 4.1 34900 34567 2.9 2.9 34774 34459 5.3 5.3 34659 34359 61354 60821 0

STATION (River Mile)SUSQUEHANNA SES-ER-OL TABLE 2.4-2 (Continued)

STAGE VELOCITY (Ft.msl)(Ft/sec)Present Pro ected Present Pro ected DIS(HARGE (Ft/sec)Present Pro ected Sunbury (122.0)Northumberland (123.5)Wolverton Sta.(128.5)Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162.4)Wapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)423.0 426.7 431.3 438.7 453.5 457.8 461.7 480.4 481.4 486.0 487.0 489.1 492.8 423.0 426.7 431.2 438.7 453.4 457.7 461.7 480.4 481.3 486.0 486.9 489.0 492.7 4.6 2.5 2.4 2.0 1.8 2.6 1.9 2.2 2.4 3.0 2.0 4.3 4.5 2.5 2.4 2.0 1.8 2.5 1.9 2.2 2.4 2.9 2.0 4'35015 34882 19326 18943 19229 18849 19060 18684 18567.18218 17909 17568 17909 17568 17475 17142 17475 17142 17457 17142 17475 17142 17379 17064 17291 16991 SUSQUEHANNA SES-ER-OL TABLE 2.4-2 (Continued)

STATION()(River Mile)S unbury (122.0)Northumberland (123.5)Wolverton Sta.(128.5)Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162.4)Wapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)424.8 424;7 429.5 429.4 436.7 436.6 450.6 450.5 455.7 455.6 459.5 459.4 47.8.5 478.3 479.4 484.5 479.3 484.5 485.1 485.0 486.9 486.8 490.3 490.2 STAGE (Ft.msl)Present Pro ected 421.8 421.8 3.4 3.3 0.9 0.9 2.4 2.4 2.2 2.1 1.8 1.8 1.4 1.4 2.1 2.0 1.5 1.4 2.0 2.0~2.0 2.0 2.2 2.2 1.5 1.5 3.8 3.7 VELOCITY (Ft/sec)Present Pro'ected 11108 10725 11054 10674 10959 10583 10638 10289 10211 9870 10211 9870 9930 9597 9930 9597 9930 9597 9930 9597 9868 9553 9811 9511 DIS(HARGE (Ft/sec)Present Pro ected 19915 19382 SUS(}UEHANNA SES-ER-OI TABLE 2.4-2 (Continued)

STATION (River Mile)STAGE (Ft.msl)Present Pro ected VELOCITY (Ft/sec)Present Pro ected DIS(HARGE (Zt/sec)Present Pro ected Sunbury (122.0)Northumberland (123.5)Volverton Sta.(128.5)Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162.4)Mapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)421.0 423.0 427.8 434.7 448.0 453.6 457.5 476.6 477.7 483.2 483.5 484.9 488.1 420.9 422.9 427.7 434.5 447.8 453.4 457.3 476.4.477.5 483.0 483.3 484.7 487.9 2.0 0.7 3.0 1.8 1.6 1.6 1.9 1.6 1.5 1.0 2.9 2.0 0.7 3.2 1.8 1.6 1.0 1.6 1.9 1.6 1.4 1.0 2.8 5277 4894 5247 4867 5194 4818 5116 4767 5012 4671 5012 4671 4944 4611 4944 4611 4944 4611 4944 4611 4929 4614 4915 4615 9734 9201

SUS(}UEHANNA SES-ER-OL TABLE 2.4-2 (Continued)

STATION()(River Mile)STAGE (Ft.msl)Present Pro ected VELOCI1Y (Ft/sec)Present Pro ected DIS(HARGE (Ft/sec)Present Pro ected Sunbury (122.0)Northumberland (123.5)Wolverton Sta.(128.5)Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162.4)Wapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)422.2 422.1 427.2 427.1 433.8 433.6 446.7 446.2 452.5 452.2 456.5.456.3 475.6 475.5 476.7 476.5 482.2 482.0 482.4 482.2 483.6 483.4 487.5 487.1 420.6 420.5 1.5 0.7 4.4 1.7 1.7 0.9 1.3 0.9 2.1 1.4 1.2 0.8 2.0 1.5 0.6 4.2 1.6 1.9 0.9 1.3 0.8, 2.3 1.3 0.7 1.9 6520 3480 3460 3425 3278 3082 3082 2953 2953 2953 2953 2924 2898 5987 3097 3080 3049 2929 2741 2741 2620 2620 2620 2620 2620 2598 STATION (River Mile)SUSQUEHANNA SES-ER-OL TABLE 2.4-2 (Continued)

STAGE VELOCITY (Ft.msl)(Ft/sec)Present Pro ected Present Pro ected DIS(HARGE (Ft/sec)Present Pro ected Sunbury (122.O)Northumberland (123.5)Wolverton Sta.(128.5)Danville (134.7)Catawissa (143.7)Bloomsburg (146.6)Almedia (150.4)Berwick (159.1)Nescopeck (160.0)Beach Haven (162.4)Wapwallopen (163.9)Plant Site (165.5)Shickshinny (169.5)42o.6 422.2 427.2 433.8 446.9 452.5 456.6 475.7 476.8 482.2 482.4 483.7 487.5 420.5 422.0 427.2 433.'6 446.3 452.3 456.4 475.5 476.6 482.1 482.2 483.5 487.1 1.4 0.7 4.4 1.7 1.6 0.9 1.3 0.9 2.1 1.4 1.2 0.8 2.0 1.4 0.7 4.3 1.7 1.9 0.9 1.3 0.8 2.2 1.4 0.7 2.0 3582 3199 3568 3188 3543 3167 3383 3034 3170 2829 3170 2829 2953 2620 3030 2697 3030 2697 3030 2697 2999 2684 2971 2671 6137 5604 SUS(}UEHANNA SES-ER-OL TABLE 2.4-2 (Continued)

Station locations are indicated as the nearest municipality or feature to the river cross-section used in the computations.

The exact cross-section location is indicated by river mile.One Foot=0.3048 meter One Foot Per Second=0.3048 meter per second One Cubic Foot Per Second=0.0283 cubic meters per second.

SUSQUEHANNA SES-ER-OL TABLE 2.4"3 MONTHLY PERCENT CHANCE OF FLOODING SUS UEHANNA RIVER UPSTREAM OF SUNBURY Month Jan Percent Chance of Floodin 6.8 Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec 7.5 40.4 19.0 8.2 2,1 2.1 1.4 1.0 3.4 2.7 5.4 (1)Sunbury is 43 miles (69 km)downstream of the site at the confluence of the Susquehanna River and the West Branch Susquehanna River.

SUSQUEHANNA SES-ER-OL SECTION TITLE VOLUME APP EN DXCIESe e s s s s e o e o s~e e~e e e e s s s s s s s s~s e s e s~s e I I I B1 AN EVALUATION OF THE COST OF SERVICE IMPACT OF A DELAY IN THE IN-SERVICE DATES OF SUSQUEHANNA SES (JANUARY 1 978).....III CURRENT LONG-RANGE FORECAST ENERGY SALES PEAK LOAD 1976-1990......................III B2 APPLICANT' FORECASTING NETHODOLOGY KMH SALES AND PEAK LOADS DECEMBER, 1976...III NATXON MIDE FU EL EilER GE NCY RES PON SE TO FPC OR DER NO 496....................

~III SUSQUEHANNA RIVER MATER ANALYSES SUNHARY..III EQUATIONS AND ASSUMPTIONS UTXLIZ ED IN THE CALCULATION OF INDIVIDUAL AND POPULATION DOS ES TO MAN....III ENVIRONMENTAL TECHNICAL SPECIFICATIONS-

-III SUSg UEHAxfH A SES ER OL Accuracy 1%f u ll scale Current full-scale deflection Input impedence Respon se Time'Rriting Type Chart Speed Channels 1.0 milliampere s 1400 ohms 0.5 seconds Curvilinear 3 in/hour 1 on each chart 2 charts/recorder All recording devices, translator=

and the digitizer are housed in a weatherproof cinderblock building.This building has thermistatically controlled heating and air conditioning.

6..1.3.1.1 5 Calibration and Yaintenance of the System All calibration and maintenance is pe formed at least semi-annually in accordance with the frequencies and producedures prescribed in the manufacturer's operating and maintenance manual.6 1.3.1.1.6 Data Analysis The analog chart records are removed every 14 days for inspection and analysis.Each chart is removed separately and placed in individual boxes labeled with date, instrument'nd level.The charts are inspected for breaks in record, time errors, power failures and other indications of system malfunction and then stored.The information gained from this inspection is used to update and verify the digital data, and to locate anomalies with any parameter.

The analog recording system provides a back-up in case of digital system failure, so that a high data recovery rate can be maintained.

Table 6.1-2, Data Recovery Bates, gives the recovery rates for each year.Digital minute data are recorded at the site on magne ic tape for analysis.At the begi.nning of each scan of data a unique identification code, the date,'hour and minute is recorded.After 14 days of recording, the tape is removed, labeled with the data period and forwarded to the Applicant, The computer 6.1-13 SUSQUEHANNA S ES-ER-OL/facility processes these tapes converting the recorded millivoltaqes into enqineerinq units.An hourly averaqe for each parameter is computed Data validity, range of hourly averages and the number of valid observations contributinq to the averages are tabulated to assist in the determination of data reliability.

Comparisons between the analog and diqital data are performed when the bi-weekly review of the digital data reveals qu'estionable or invalid data.Temperature and dew point hourly averages are computed using the f ollowinq scalar equation: B.=1 Z r.B..n.j ji i=1 where: the average hourly value for the jth variable (in physical units);B..the total number of minute observations during the hour (normally 60), but if n is less than 15 f or that hour, data are considered to be missing;the i" minute observation on the 3+" variable (millivolts):

the conversion factor to change the j<hvariable from millivolts into physical units.After wind speed (WS)and wind direction (WD)are converted from millivolts they are related in the followinq manner: If WS is invalid (999)then WD is marked invalid (999)and vice versa.If WS)threshold (non-calm) and WD=0 (implying calm)then WD is set to 360~(North)If WS (threshold (calm)and WD)0 (implying non-calm)then WD is set to 0o (calm)Hourly averages are computed as scalars for wind speed.Wind direction averages are, determined as follows: If the associated averaqe wind speed is greater than 1.34112 meters/sec, (3 mph), average WD is determined by vector analysis (where WS and WD for each minute determines a vector).6 1-14 S USQU EH A NNA S ES-ER-OL APPENDIX B2 APPLICANT~S PORECASTING METHODOLOGY KMH SALES AND PEAK LOADS December, 1976 INTRODUCTION The PP&L energy model forecasts KWH consumption for each of the major groups in the PP&L Service Area;i.e., o RESIDENTIAL o COMMERCIAL o INDUSTRIAL o RESALE, STREET LIGHTING AND RAILROAD An econometric model is developed by considering the determinants for each of the sectors.While the model, by necessity, is a simplification, it captures the crucial linkages between sector activity and KWH sales, providing the user with a structural framework for forecasting.

Through the model a user can produce a forecast of sales for each of the sectors consistent with an economic outlook.More importantly the impact of alternative economic scenarios can be tested.In arriving at a forecast, the model utilizes information and forecasts of the U.S.economy, the national energy market, the Central Eastern Pennsylvania (C.E.P.)economy, local weather conditions and company policy.This information is obtained from a combination of existing forecasting services and reviews with PP&L Energy Consultants.

The PP&L model builds from that point, measuring the impact of the national economic outlook on the C.E.P.region.This outlook is then combined with assumptions about weather conditions and company policy to produce a forecast of energy sales to each of the sectors.MODEL STRUCTURE In developing a model of electric energy consumption for a particular region it is important to, Qrst, define the demand conditions present in that service area, and second, measure their impact on sales to each of the sectors.The PP&L energy model is developed within this two-stage process.In the first stage of the model, demand conditions are defined, i.e., climatic conditions, the economic environment, energy prices, and company policy.Weather, energy'costs and company policy are all exogenous inputs to the model.The economic conditions are developed endogenously through an'conometric frame-work.The second stage measures the impact of these demand conditions on each sector through a set of econometric equations, relating sales to those factors that are known to affect growth.The general flow of the model is given.in Figure I.

The service area economic model is linked to the DRI Macro Economic Model, bridging the gap between the national economy and local sales by highlighting regional characteristics (i.e., industrial mix, growth trends, demographic mix, etc.)and by including explicitly the impact of the national economy on the region.This linkage is primarily through the industrial sector.For example, the steel industry in the C.E.P.region serves a national market, therefore, their sales depend on demand conditions in the nation.In developing a model to forecast the growth of the steel industry in the region it is necessary to include national economy.As another ex-ample, the housing industry in the area is heavily dependent on local wealth and demographic mix, but a depressed steel industry would lower local wealth thereby slowing housing growth.The function of the service area model is to liter these national conditions so as to measure their impact on the local economy.Thus, the electric use forecast is developed in the following way.A fore-cast of the national economy, developed through the DRI Macro Model, is accepted or altered to reflect PP&L.'s thinking.That forecast is fQtered through the service area economic model to determine local economic conditions.

Again the user has the option of accepting the results or altering them where he deems necessary.

The economics are combined with assumptions about energy prices, expected weather conditions and company policy to define the local demand conditions.

Finally, this information determines the expected level of megawatthour sales.At each stage the forecaster has the ability to adjust the output of the model before going on.It allows the user the required Qexibility to make the model a useful tool.The next three sections detail the methodology used in developing the economic and energy models.SERVICE AREA ECONOMIC MODEL The Central Eastern Pennsylvania (C.E.P.)economic model is constructed to highlight the regional economy within the PP&L service area.It provides infor-mation about four major economic areas: A.INDUSTRIAL SECTOR B.COMMERCIAL SECTOR C.WAGES&PERSONAL INCOME.D.HOUS ING The general Qow of the model is depicted in Figure II.Briefly, the model unfolds as follows.The industrial sector, through employment, is linked to the national economy.The tightness of the local labor market, along with inflationary conditions, determine the level of manufacturing wages.In the next stage, employ-ment in the commercial sector and per capita personal income are simultaneously determined; their levels are dependent on industrial activity and are interdependent with each other.Finally, population of the house-owning age group is combined with local wealth and employment conditions, and national information on the Qnancial markets to determine the housing market growth.A brief description of each area follows.0 A.INDUSTRIAL SECTOR A region's manufacturing sector, primarily its exporting industries, provide the major link between the national and regional economies.

Thus, we would expect this sector to follow the national patterns given that it serves a national market.However, we expect the local industries to maintain regional characteristics as well, from the standpoint of locational decisions on the part of entering/exiting manufacturing concerns, In modelling manu-facturing employment in the PP&L service area every attempt was made to include these two aspects: linkage with the national economy and regional locational decisions.B.COMMERCIAL SECTOR The type of services provided and products sold within the commercial sector are quite similar across different regions of the country.However, the growth of this sector within a region is heavily dependent upon the local economy.In developing the commercial employment equations, the growth in each of these sectors was compared to their breakdowns nationally.

The relative growth of the area was then compared to the relative U.S.growth in population and per capita income.C.WAGES, PRICES, AND PERSONAL INCOME Manufacturing average hourly earnings and total personal income for the service area are forecasted within the C.E.P.economic model, building from the employment situation in the manufacturing and commercial sectors.In addition, a forecast of local inflation conditions is developed directly from the inflation conditions of the nation.D.HOUSING SECTOR The growth in the housing stock is an important determinant of residential sales.Therefore, in the economic model, we explictly model household formations in the service area.In developing this sector we have a choice of two available data series, household permits from the federal government and new dwelling unit statistics from PPaL records.The dwelling unit data, considered more reliable and easier to monitor, was used.The long-run demand for housing is hypothesized to be a'unction of the population of the house-owning age group and the level of household wealth.IV.RESIDENTIAL SECTOR The residential model has been developed to forecast sales to the two major classes of residential service;viz., electrically heated homes and general residential.

In doing so the model is divided into two blocks: o CUSTOMER BLOCK o USAGE BLOCK In the customer block the number.of residential customers under each of the services is determined.

The'usage block determines the average kWh usage per customer under each of the, services.Total residential usage is obtained by summing the product of customer stock and per customer usage in each of the groups.Customer Block Total residential customers in any period is equal to the number in the previous period, plus the new units coming on, less the depreciation of the existing stock.In estimating our usage per customer equations, the impact of the following determinants was measured.o HOUSEHOLD INCOME o PRICE OF ELECTRICITY o PEOPLE PER HOUSEHOLD o WEATHER CONDITIONS o CONSERVATION EFFORTS V.Figure III shows the relationships that are considered in modelling this sector.COMMERCIAL SECTOR The Commercial Sector presents a difficult modelling task to the forecaster.

Over the past 10 to 15 years it has shown steady growth, becoming an increasing portion of total sales;yet little information is available over this interval on the type of load served.The best that can be done in lieu of commercial surveys and expanded data collection is to include in, the model those economic indicators that best depict the growth of these customers.

The modelling task is not one of obtaining satisfactory summary statistics, they come rather easily, but rather to be sure that the real determinants and indicators of growth are in the'model.

In addition to the overall growth, the price of electricity, weather conditions and conservation are considered important determinants of sales and are included.Sales to the commercial sector are collected by four major classes: o Wholesale and Retail Trade o Financial and Personal Services o Other Commercial o Small Commercial The general outline of estimating this sector is exhibited in Figure IV.

INDUSTRIAL SECTOR The Industrial Model was developed to forecast KWH sales to fourteen major industrial classes.The sales forecast for the industrial sector is'the aggregation of these fourteen cia'sses, the breakdown of which is given in the table below and the flow diagram.shown as Exhibit V.INDUSTRIAL SECTOR BREAKDOWN OF INDUSTRIAL CLASSES SIC INDUSTRY 20 22 23 27 28 324 33 (less 331)331 35 36 11512 Food&Kindred Products Textile Mill Products Apparel Printing&Publishing Chemicals&Allied Products Cement Primary Metals (except Steel)Steel Manufacturing Non-Electrical Machinery Electrical Riachinery Other Metal Products>Other General Industry2 S mall Industrial Coal Mining Note: l.Includes Mining (SIC 10), Ordnance (SIC 19), Fabricated Metals (SIC 34), Transportation Equipment (SIC 37)and Instruments (SIC 38).2.Includes Oil a Gas Extractions (SIC 13), Mining a Quarrying (SIC 14), Tobacco Products (SIC 21), Lumber and Wood Products (SIC 24), Furniture and Fixtures (SIC 25), Paper and Allied Products (SIC 26), Petroleum Refining (SIC 29), Rubber and Plastics (SIC 30), Leather and Products (SIC 31), Stone, Clay and Glass, less Cement (SIC 32.less 324), Miscellaneous Industries (SIC 39).In the industrial model, four major factors were considered:

o Production Activity o Factor Substitution o Technological Change o Conservation VII.

SUMMARY

In summary, the PP5L Econometric Model forecasts th'e short and long-term kWh consumption for the major consuming sectors, in the.PPaL Service Area.It utilizes forecasts from the DRI Macro Model togetherwith regional economic, demo-graphic, and climatic conditions-to determine a scenario of the service area economy.Assumptions about the price of electricity and competing fuels, weather expectations, the working age population, and technological changes are then made, from which point the model produces a kWh forecast.Outlooks are also prepared by PPaL Energy Consultants.

In the residential sector, the model forecasts kWh sales for Electrically Heated Homes and General Residential Service.For both of these classes, sales is the product of the number of customers and usage per.customer.

The number of customers is a function of employment in the service area, real disposable income, new dwelling units, the price of electricity and competing fuels, and new mortgage commitments.

Usage per customer is determined, for the most part, by the real price of electricity, real disposable income, and weather.The model, which develops the mathematical relationships among these variables, then fore-casts residential sales.Commercial sales, which are segregated into four categories, are a function of commercial employment in the service area, real disposable income, the real price of electricity, and weather.The growth in commercial demand is positively related to the first two variables while negatively related to the third.By solving a series of equations, the model'determines the kWh consumption in the commercial sector.The forecast of industrial sales makes use of estimates of industrial output, which in turn is a function of manufacturing employment.

Manufacturing employment, by two-digit SIC Codes in the PPaL service area depends upon current levels of employment and the level of production for a particular industry.Industrial output in our service area is defined as the Federal Reserve Board Production Index times the ratio of PPSL employment to U~S.employment.

Sales to the fourteen industrial SIC groups are mainly determined by finding the relationship of kWh sales to service area industrial output, the relative price of electricity to fuel oil, the relative price of electricity to natural gas, and any technological changes that might occur.No model, regardless of how well it is specified, will forecast perfectly.

There will be exogenous events, such as large new loads or changes in company or government policy, that the model is unable to pick up.In these cases, the results of the model can be modified to the desired level by judgment.VIII.PEAK LOAD FORECAST In order to adequately provide for our customers'emands for electricity, adequate generating capacity must be available.

The amount of capacity required is determined by forecasting summer and winter system peak loads for ten to fifteen years into the future.Summer and winter system peaks are forecasted because it is during these periods that the greatest demands are made on our system.Air conditioning load causes the summer peaks, and lighting and space heating loads are responsible for those in the winter.

PPEL's estimating procedure produces summer and winter system peak loads by developing the contribution made by each rate class.The term"rate class" means all customers served under similar rate schedules.

The sale of energy forecast developed by revenue classes is reallocated to rate classes using observed historical relationships.

Load study data is then brought into the estimation process.Our load studies are designed to determine the load characteristics of a specific class of service.When meters are of the watt-hour type, stratified random samples of customers within kilowatt-hour ranges are used.In the case of most general service sample customers (up to 7000 kw with demand meter billing), load factor ranges within each rate class are used.Larger commercial and industrial customers are studied individually.

Daily load curves for the days of summer and winter system peak are derived for every stratum of each rate class for an average customer.For customers studied by kilowatt-hour ranges, demand per customer data for each stratum of each rate class are multiplied by the number of customers in the universe of that stratum to obtain a universe daily load curve.The number of customers in a stratum is obtained from the Company's bill frequency distributions.

This can also be done for years other than the load study test year because the load characteristics of a kWh or load factor stratum remain fairly constant with only the number of customers in a stratum changing from year to year.Daily load curves for load factor stratum are stated as ratios of customer monthly maximum demand.These are applied to the sum of customer demands in each load factor stratum as determined from an hours-use distribution to obtain the universe daily load curve.For an historical year the strata of a given rate class are added together to form the daily load curve for the universe of that rate class.The rate class load curves for the days of summer and winter system peak of a given year are corrected for losses to the net generation level and added together to form the summer and winter load curves for the system.The result is checked against actual peak loads.Using these techniques we have developed rate class contributions to summer and winter system peaks historically for selected hours of the day.The ratio between class contribution to system peak and annual sales to that class is calculated for each rate class at the time of summer and winter system peak, for every historical period analyzed.The trend of this ratio for either a summer or a winter syst'm peak is fairly constant over time.For a given class the trend of this ratio for the time of both summer and winter system peak is projected through time.By applying the appropriate ratios to the predicted annual sales of any future year, that class'ontribution to summer and winter peak is forecasted.

The system peak for a specific time period is obtained by adding together the projected class contributions to system peak.

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t C Q$5NATICN I I IN cvsnu~c Bmoc IIIiIH CCRC.NISI~TOTAL~WAW HO@%.SALES IMDV5TTRIAL ScCTA Exhibit V SUSQU EH ANNA SES-ER-OL contaminated by airborne radioiodine is a potential source of exposure.Samples from milk animals are considered a better indicator of radioiodine in the environment than vegetation.

If the census reveals milk animals are not present or are unavailable for sampling, then veqetation may be sampled.The 500-sq.ft.garden, considering 20%used for growing green leafy vegetables and a vegetation yield of 2 kg/m>will produce the 26 kq/yr assumed in~Re ula~tor Guide 1.109 (March 1974)for child consumption of leaf y veqetation.

The option to consider the garden to be at the nearest residence is conservative and those locations may be used to calculate doses due to radioactive ef fluent releases in place of the actual locations which would be determined by the census.The permission of deviations from the sampling schedule is based on the recognition of unavoidable practical difficulties which in the absence of the permitted deviations would result in violation of the specifications.

The requirement for the participation in the EPA cross-check program, or similar program, is based on the need for independent checks on the precision and accuracy of the measurements of radioactive material in environmental monitorinq in order to demonstrate the validity of the results.~Re oeting Requirement A.Annual Environmental Operatinq Report, Part B, Radiological.

A report on the radiological environmental sur veillance proqram for the previous calender year shall be submitted to the Director of the NRC Regional Office (with a copy to the Director, Office of Nuclear Reactor Requlation) as a separate document in May of each year.The period of the first report shall begin with the date of initial criticality The report shall include a.summary (format of Table F-1, Environmental Monitoring Program Summary)interpretations, and statistical evaluation of the results of the radiological environmental surveillance activities for the report period, includinq a comparison with operational, controls, preoperational studies (as appropriate) and previous environmental surveillance reports and an assessment of the observed impacts of the station operation on the environment.

In the event that some results are not available the report shall be submitted noting and explaining the reasons for the missinq results.The missing data shall be submitted as soon as possible in a supplementary report.

S US QU EHA N NA S ES-ER-OL The reports shall include either explicitly or by reference to other documentation, the following:

a summary description of the radiological environmental monitorinq program including sampling methods for each sample type, size and physical characteristics of each sample type, sample preparation methods analytical methods, and measurinq equipment used;a map of all sampling locations..the results of the land use censuses and the results of the Applicant's participation in the Environmental Protection Agency's Environmental Radioactivity Laboratory Intercomparisons Studies (Crosscheck)

Proqram.B.Non-routine Radiological Fnvironmental Operatinq Reports If a confirmed measured radionuclide concentration in an environmental sampling medium averaged over any quarter samplinq period exceeds the reporting level given in Table F-4, Reportinq Levels.for Non-Routine Operation, a written report shall be submitted to the Director of the NBC Regional Office (with a copy to the Director, Office of Nuclear Reactor Regulation) within 30 days from the end of the quarter.A confirmatory reanalysis of the original, a duplicate or a new sample may be desirable, as appropriate.

The results of the confirmatory analysis shall be completed at the earliest time consistent with the analysis, but in any case within 30 days except in the case of the strontium analysis.Zf it can be demonstrated that the level is not a result of station effluents (i.e., by comparison with control station or preoperational data)a report need not be submitted, but shall be discussed in the annual report.If radionuclides other than those in Table-F-4 are detected and are due from station effluents, a reporting level is exceeded if the potential annual dose to an individual is equal to or greater than the design objective doses of 10 CFR Part 50, Appendix I This report shall include an evaluation of a release conditions, environmental factors or other aspects necessary to explain the anomalous result SUSQUEHANNA SFS-ER OL TABLE F-2 SUSQUEHANNA SES OPERATIONAL RADIOLOGICAL ENVIRONMENTAL HONITORING PROGRAH Sam~le T pe Air Particulates SS-AP-551 SS-AP-1152 SS-AP-9A1 SS-AP-12E1 SS-AP-7Hl Air Iodine SS-AI-551 SS-AI-1152 SS-AI-9A1 SS-AI-12El SS-AI-7H1 Surface Water SS-SW-5S2 SS-SW-12F1 Dr~inkin Water SS-PWT-12F2 SS-PWT-12H2 Fish**SS-AQF-6AI SS-AQF-2G1 Sediment SS-AQS-llcl Milk SS-H-5B1 SS-M-12B1 SS-H-1282 SS-H-7H2 Location++North of I.A.SW corner of si te Near Transmission Field Berwi ck Hospital PPEtL Roof North of I.A.SW corner of site Near Transmission Field Berwick Hospital PPSL Roof At I.A.Berwick Bridge Berwick Water Co.(treated)Danvi lie Water Co.(treated)Outfall Upstream Hess Is, area Farm Schultz Farm Young Farm Crytal Springs Dairy Collection F~PB UMC*SA SA 2/H~Anal sis Gross Beta Galena Emitters I-131 Gama Emitters H-3 Gross Beta Gamma Emi tters H-3 Gama Emi tters Gamma Emi tters I-131 Gama Emitters Analyti cal F~re Cene*W QC H QC SA SA 2/H 2/H Uni ts pCi/m3 pCi/m pCi/m pCi/1 pCi/1 pCi/1 pCi/1 pCi/1 pCi/g(wet)

PCi/9(dry) pCi/1 pCi/1 SUSQUEHANNA SES-ER-OL TABLE F-2 (cont.)SUSQUEHANNA SES OPERATIONAL RADIOLOGICAL ENVIRONMENTAL HONITORING PROGRAH~Sam le T e Food Products SS-FP-5B1 Direct Radiation SS-ID-3S2 SS-I D-4S1 SS-ID-551 SS-ID-7S1 SS-ID-11S2 SS-I D-9AI SS-ID-12E1 SS-ID-7HI Location++Farm Susquehanna River Susquehanna River North of I.A.On 230 KV Tower On 230 KV Tower Near Transmission Field Berwick Hospital PP&L Roof Collection

~Fee mene*~Anal sis Ganma Emitters Gama Dose Analytical

~Fre mene*Uni ts pCi/g(wet) mrem/std.mo Frequency Codes: W=Weekly;H=Monthly;Q=Quarterly; SA=Semi-Annual; A=Annual;2/H=twice each month;C Composite.

Important classes of fish will be analyzed separately.(bottom feeders and game fish)Hilk collected and analyzed semi-monthly from April through October-monthly during other months.Shown in Figure.

SUSQUEHANNA SES ER OL TABLE F-3 DETECTION CAPABILITIES FOR ENVIRONMENTAL SAMPLE ANALYSIS MINIMUM DETECTABLE LEVEL (MDL)Analys is Water (pCi/l)Airborne Particulate or Gas (pCi/m')Fish (pCi/kg-wet)

Mi 1 k Food Products Sediment (pCi/1)(pCi/kg-wet)(pCi/kg-dry)

Gross Beta H-3 Mn-54 Fe-59 Co-58,60 Zn-65 ZrNb-95 I-131 Cs-134,137 BaLa-140 200 10 20 10 20 0.3 10 10 7 x 10 5x10 5 x 10 85 170 85 170 85 5c 10 10 16c,d 50 100 SUSQUEHANNA SES-ER-OL Table F-3 (Cont'd)~Acceptable detection capabilities for thermoluminescent dosimeters used for environmental measurements are given in Regulatory Guide 4.13, July 1977.Indicates acceptable detection capabilities for radioactive materials in environmental samples.These detection capabilities are tabulated in terms of the minimum detectable level (MDLs).The NOL is defined, for purposes of this Table, as that concentration of radioactive material in a sample that will yield a net count which is different from the background count by three times the standard deviation after background count.For a particular measurement system (which may include radiochemical separation):

MDL=3 00 Sb E x V x 2.22 x Y x exp(-X t)where, NOL is minimum detectable level as defined above (as pCi per unit mass or volume)Sb is the standard deviation of the background counting rate or of the counting rate of a blank sample as appropriate (as counts per minute)E is the counting efficiency (as counts per disintegration)

V is the sample size (in units of mass of volume)2e22 is the number of disintegrations per minute per picocurie Y is the fractional radiochemical yield (when applicable) is the radioactive decay constant for the particular radionuclide is the elapsed time between sample collection and counting The value of S used in the calculation of the NOL for a particular measurement system should e based on the actual observed variance of the background counting rate or of the counting rate of the blank samples (as appropriate) rather than on an unverified theoretically predicated variance.In calculating the MDL for a radionuclide determined by gama-ray spectrometry, the background should include the typical contributions of other radionuclides normally present in the sample (e.q., potassium-40 in milk samples).Typical values of E,V,Y, and t should be used in the calculation.

It should be recognized that the NOL is defined as~a riori (before the fact)limit representing the capability of a measurement system and not as f t f ill i f p SUSQUEHANNA SES-ER-OL Table F-3 (Cont'd)c.MDLs for I-131 in water, milk and other food products correspond to one-quarter of the Appendix I (10 CFR Part 50)design objective dose-equivalent of 15 mrem/year using the assumptions given in Regulatory Guide 1.109 except for an infant consuming 330 1/yr of drink water.d.MDL for leafy vegetables.